dylanhogg/awesome-python · Datasets at Hugging Face

1,818

gui

https://github.com/beeware/toga

['toolkit', 'gui']

null

[]

null

beeware/toga

toga

3,998

673

85

Python

https://toga.readthedocs.io/en/latest/

A Python native, OS native GUI toolkit.

beeware

2024-01-13

2014-08-01

495

8.067455

https://avatars.githubusercontent.com/u/19795701?v=4

A Python native, OS native GUI toolkit.

[]

['gui', 'toolkit']

2024-01-11

[('hoffstadt/dearpygui', 0.7974780201911926, 'gui', 2), ('kivy/kivy', 0.692936360836029, 'util', 0), ('parthjadhav/tkinter-designer', 0.6891065239906311, 'gui', 1), ('r0x0r/pywebview', 0.6624377965927124, 'gui', 1), ('urwid/urwid', 0.6368706822395325, 'term', 0), ('wxwidgets/phoenix', 0.6360959410667419, 'gui', 1), ('dddomodossola/remi', 0.6270981431007385, 'gui', 1), ('pysimplegui/pysimplegui', 0.6206801533699036, 'gui', 1), ('willmcgugan/textual', 0.5924068689346313, 'term', 0), ('adamerose/pandasgui', 0.590601921081543, 'pandas', 1), ('alexmojaki/snoop', 0.5817451477050781, 'debug', 0), ('pyglet/pyglet', 0.572860598564148, 'gamedev', 0), ('tkrabel/bamboolib', 0.5691761374473572, 'pandas', 0), ('pyston/pyston', 0.5686622262001038, 'util', 0), ('beeware/briefcase', 0.5662544965744019, 'util', 0), ('holoviz/panel', 0.5590908527374268, 'viz', 1), ('jquast/blessed', 0.5573833584785461, 'term', 0), ('pypy/pypy', 0.5504774451255798, 'util', 0), ('holoviz/holoviz', 0.5480042099952698, 'viz', 0), ('python/cpython', 0.5390973091125488, 'util', 0), ('gradio-app/gradio', 0.5377219915390015, 'viz', 0), ('eleutherai/pyfra', 0.5376284718513489, 'ml', 0), ('pytoolz/toolz', 0.5362921953201294, 'util', 0), ('google/gin-config', 0.5335937738418579, 'util', 0), ('samuelcolvin/python-devtools', 0.5332743525505066, 'debug', 0), ('kubeflow/fairing', 0.5289453268051147, 'ml-ops', 0), ('pallets/click', 0.5282005667686462, 'term', 0), ('pyqtgraph/pyqtgraph', 0.5267707109451294, 'viz', 0), ('fastai/fastcore', 0.5267270803451538, 'util', 0), ('goldmansachs/gs-quant', 0.5231086611747742, 'finance', 0), ('erotemic/ubelt', 0.5228415727615356, 'util', 0), ('huggingface/huggingface_hub', 0.5219206213951111, 'ml', 0), ('indygreg/pyoxidizer', 0.5212326645851135, 'util', 0), ('klen/py-frameworks-bench', 0.5207023024559021, 'perf', 0), ('landscapeio/prospector', 0.517236590385437, 'util', 0), ('google/python-fire', 0.5118656754493713, 'term', 0), ('pympler/pympler', 0.5115267634391785, 'perf', 0), ('python-rope/rope', 0.5071592330932617, 'util', 0), ('micropython/micropython', 0.5063884258270264, 'util', 0), ('libtcod/python-tcod', 0.5042990446090698, 'gamedev', 0), ('weaviate/weaviate-python-client', 0.5031599998474121, 'util', 0)]

256

7

null

35.79

200

127

115

0

4

7

4

200

486

90

2.4

58

748

ml

https://github.com/marqo-ai/marqo

[]

null

[]

null

marqo-ai/marqo

marqo

3,856

162

35

Python

https://www.marqo.ai/

Vector search for humans. Also available on cloud - cloud.marqo.ai

marqo-ai

2024-01-13

2022-08-01

78

49.345521

https://avatars.githubusercontent.com/u/103185353?v=4

Vector search for humans. Also available on cloud - cloud.marqo.ai

['chatgpt', 'clip', 'deep-learning', 'gpt', 'hnsw', 'information-retrieval', 'knn', 'large-language-models', 'machine-learning', 'machinelearning', 'multi-modal', 'natural-language-processing', 'search-engine', 'semantic-search', 'tensor-search', 'transformers', 'vector-search', 'vision-language', 'visual-search']

2024-01-11

[('qdrant/qdrant', 0.7367421984672546, 'data', 4), ('cheshire-cat-ai/core', 0.6071776151657104, 'llm', 1), ('activeloopai/deeplake', 0.6008663177490234, 'ml-ops', 4), ('milvus-io/bootcamp', 0.5712332725524902, 'data', 1), ('googlecloudplatform/vertex-ai-samples', 0.5693247318267822, 'ml', 0), ('docarray/docarray', 0.5685033798217773, 'data', 4), ('weaviate/demo-text2vec-openai', 0.5455718040466309, 'util', 1), ('jina-ai/jina', 0.5435925126075745, 'ml', 2), ('mindsdb/mindsdb', 0.5285826325416565, 'data', 3), ('lancedb/lancedb', 0.5243335366249084, 'data', 2), ('rcgai/simplyretrieve', 0.5212767124176025, 'llm', 3), ('neuml/txtai', 0.5169413089752197, 'nlp', 7), ('tensorflow/tensorflow', 0.5045498013496399, 'ml-dl', 2), ('alirezadir/machine-learning-interview-enlightener', 0.5009713768959045, 'study', 2)]

30

2

null

7.23

115

93

18

0

18

17

18

115

33

90

0.3

58

429

viz

https://github.com/holoviz/panel

[]

null

[]

null

holoviz/panel

panel

3,647

420

53

Python

https://panel.holoviz.org

Panel: The powerful data exploration & web app framework for Python

holoviz

2024-01-14

2018-08-23

283

12.854481

https://avatars.githubusercontent.com/u/51678735?v=4

Panel: The powerful data exploration & web app framework for Python

['bokeh', 'control-panels', 'dashboards', 'dataapp', 'datascience', 'dataviz', 'gui', 'holoviews', 'holoviz', 'hvplot', 'jupyter', 'matplotlib', 'panel', 'plotly']

2024-01-13

[('plotly/dash', 0.7759690284729004, 'viz', 2), ('bokeh/bokeh', 0.7603949308395386, 'viz', 2), ('holoviz/holoviz', 0.7308956384658813, 'viz', 4), ('man-group/dtale', 0.7240487337112427, 'viz', 0), ('plotly/plotly.py', 0.7203231453895569, 'viz', 1), ('kanaries/pygwalker', 0.6920881271362305, 'pandas', 2), ('holoviz/hvplot', 0.6510308980941772, 'pandas', 2), ('mwaskom/seaborn', 0.6487950086593628, 'viz', 1), ('residentmario/geoplot', 0.6484428644180298, 'gis', 1), ('eleutherai/pyfra', 0.6469884514808655, 'ml', 0), ('giswqs/geemap', 0.6401718258857727, 'gis', 2), ('federicoceratto/dashing', 0.6392130851745605, 'term', 0), ('matplotlib/matplotlib', 0.6378490328788757, 'viz', 1), ('vizzuhq/ipyvizzu', 0.6363608837127686, 'jupyter', 2), ('pyqtgraph/pyqtgraph', 0.6308204531669617, 'viz', 0), ('polyaxon/datatile', 0.6254085302352905, 'pandas', 2), ('adamerose/pandasgui', 0.6248031854629517, 'pandas', 1), ('gradio-app/gradio', 0.6235347390174866, 'viz', 0), ('cuemacro/chartpy', 0.6215455532073975, 'viz', 3), ('jakevdp/pythondatasciencehandbook', 0.6207575798034668, 'study', 1), ('tkrabel/bamboolib', 0.620628833770752, 'pandas', 0), ('opengeos/leafmap', 0.6154477596282959, 'gis', 3), ('pandas-dev/pandas', 0.6123045682907104, 'pandas', 0), ('willmcgugan/textual', 0.6071124076843262, 'term', 0), ('lux-org/lux', 0.6041948795318604, 'viz', 1), ('contextlab/hypertools', 0.6038259267807007, 'ml', 0), ('maartenbreddels/ipyvolume', 0.597214937210083, 'jupyter', 2), ('vaexio/vaex', 0.5968863368034363, 'perf', 0), ('krzjoa/awesome-python-data-science', 0.5961334705352783, 'study', 0), ('hoffstadt/dearpygui', 0.5953347086906433, 'gui', 1), ('voila-dashboards/voila', 0.5938263535499573, 'jupyter', 1), ('dylanhogg/awesome-python', 0.5920050144195557, 'study', 1), ('wesm/pydata-book', 0.5906403064727783, 'study', 0), ('masoniteframework/masonite', 0.5894260406494141, 'web', 0), ('altair-viz/altair', 0.5875522494316101, 'viz', 0), ('quantopian/qgrid', 0.5826691389083862, 'jupyter', 0), ('scitools/iris', 0.5823258757591248, 'gis', 0), ('klen/muffin', 0.5814103484153748, 'web', 0), ('ranaroussi/quantstats', 0.5793597102165222, 'finance', 0), ('mito-ds/monorepo', 0.5779578685760498, 'jupyter', 1), ('wxwidgets/phoenix', 0.5708284378051758, 'gui', 1), ('mckinsey/vizro', 0.5707153081893921, 'viz', 1), ('graphistry/pygraphistry', 0.567793607711792, 'data', 1), ('pallets/flask', 0.5666216611862183, 'web', 0), ('datapane/datapane', 0.5654339790344238, 'viz', 0), ('clips/pattern', 0.5649107098579407, 'nlp', 0), ('parthjadhav/tkinter-designer', 0.5603848099708557, 'gui', 1), ('beeware/toga', 0.5590908527374268, 'gui', 1), ('pysimplegui/pysimplegui', 0.5573893189430237, 'gui', 1), ('saulpw/visidata', 0.5565743446350098, 'term', 0), ('has2k1/plotnine', 0.5538381338119507, 'viz', 0), ('geopandas/geopandas', 0.550635039806366, 'gis', 0), ('goldmansachs/gs-quant', 0.5493612289428711, 'finance', 0), ('pytables/pytables', 0.544653058052063, 'data', 0), ('reflex-dev/reflex', 0.5437241196632385, 'web', 0), ('aws/graph-notebook', 0.5436458587646484, 'jupyter', 1), ('gaogaotiantian/viztracer', 0.5426017045974731, 'profiling', 0), ('wandb/client', 0.5422174334526062, 'ml', 0), ('falconry/falcon', 0.5421604514122009, 'web', 0), ('webpy/webpy', 0.5416973829269409, 'web', 0), ('bloomberg/ipydatagrid', 0.5404045581817627, 'jupyter', 0), ('r0x0r/pywebview', 0.5402711629867554, 'gui', 1), ('scrapy/scrapy', 0.5401167869567871, 'data', 0), ('python-visualization/folium', 0.5396947860717773, 'gis', 0), ('hydrosquall/tiingo-python', 0.5386637449264526, 'finance', 0), ('fastai/fastcore', 0.5372098684310913, 'util', 0), ('jupyterlab/jupyterlab-desktop', 0.5330305695533752, 'jupyter', 1), ('enthought/mayavi', 0.5323789715766907, 'viz', 0), ('ibis-project/ibis', 0.5315485596656799, 'data', 0), ('rapidsai/jupyterlab-nvdashboard', 0.5303380489349365, 'jupyter', 0), ('rstudio/py-shiny', 0.5275716781616211, 'web', 0), ('matplotlib/mplfinance', 0.5236456394195557, 'finance', 1), ('pyvista/pyvista', 0.5228663682937622, 'viz', 0), ('holoviz/geoviews', 0.521112859249115, 'gis', 2), ('hazyresearch/meerkat', 0.5195465683937073, 'viz', 0), ('malloydata/malloy-py', 0.5195130109786987, 'data', 0), ('dagworks-inc/hamilton', 0.5194111466407776, 'ml-ops', 0), ('reloadware/reloadium', 0.5191416144371033, 'profiling', 0), ('dlt-hub/dlt', 0.5181348323822021, 'data', 0), ('simonw/datasette', 0.5158277153968811, 'data', 0), ('bottlepy/bottle', 0.5157780647277832, 'web', 0), ('pygraphviz/pygraphviz', 0.5157747268676758, 'viz', 0), ('roniemartinez/dude', 0.5136420726776123, 'util', 0), ('pmaji/crypto-whale-watching-app', 0.5126122236251831, 'crypto', 1), ('cohere-ai/notebooks', 0.5109737515449524, 'llm', 0), ('raphaelquast/eomaps', 0.5107569098472595, 'gis', 1), ('kivy/kivy', 0.5100237131118774, 'util', 0), ('holoviz/datashader', 0.5079904198646545, 'gis', 1), ('pylons/pyramid', 0.507599949836731, 'web', 0), ('visgl/deck.gl', 0.5066721439361572, 'viz', 0), ('pyglet/pyglet', 0.5058193206787109, 'gamedev', 0), ('westhealth/pyvis', 0.5053226947784424, 'graph', 0), ('imageio/imageio', 0.504224419593811, 'util', 0), ('flet-dev/flet', 0.5036301016807556, 'web', 0), ('ipython/ipyparallel', 0.5028029084205627, 'perf', 1), ('twopirllc/pandas-ta', 0.5016809105873108, 'finance', 0), ('python/cpython', 0.5009852051734924, 'util', 0), ('alphasecio/langchain-examples', 0.500730037689209, 'llm', 0), ('alexmojaki/heartrate', 0.5002499222755432, 'debug', 0), ('timofurrer/awesome-asyncio', 0.5001717805862427, 'study', 0)]

156

3

null

19.56

717

455

66

0

19

102

19

714

1,170

90

1.6

58

221

jupyter

https://github.com/jupyterlite/jupyterlite

[]

null

[]

null

jupyterlite/jupyterlite

jupyterlite

3,470

258

40

TypeScript

https://jupyterlite.rtfd.io/en/stable/try/lab

Wasm powered Jupyter running in the browser 💡

jupyterlite

2024-01-10

2021-03-27

148

23.378248

https://avatars.githubusercontent.com/u/81094398?v=4

Wasm powered Jupyter running in the browser 💡

['jupyter', 'jupyterlab', 'jupyterlab-extension', 'lite', 'pyodide', 'wasm', 'webassembly']

2024-01-10

[('voila-dashboards/voila', 0.6913954615592957, 'jupyter', 2), ('jupyterlab/jupyterlab', 0.6288254261016846, 'jupyter', 2), ('jupyterlab/jupyterlab-desktop', 0.6264117956161499, 'jupyter', 2), ('jupyter/notebook', 0.6035483479499817, 'jupyter', 1), ('jupyter-widgets/ipywidgets', 0.5854482650756836, 'jupyter', 1), ('pyodide/pyodide', 0.5671476721763611, 'util', 2), ('maartenbreddels/ipyvolume', 0.5511241555213928, 'jupyter', 1), ('mwouts/jupytext', 0.5492159128189087, 'jupyter', 2), ('mamba-org/gator', 0.5473883152008057, 'jupyter', 1), ('cherrypy/cherrypy', 0.5396081805229187, 'web', 0), ('jupyter-widgets/ipyleaflet', 0.539129376411438, 'gis', 2), ('ipython/ipykernel', 0.5333779454231262, 'util', 1), ('computationalmodelling/nbval', 0.5270730257034302, 'jupyter', 0), ('vizzuhq/ipyvizzu', 0.5260722041130066, 'jupyter', 1), ('jupyter/nbviewer', 0.5257112979888916, 'jupyter', 1), ('jupyter-lsp/jupyterlab-lsp', 0.5251054763793945, 'jupyter', 3), ('jupyter/nbformat', 0.5237820744514465, 'jupyter', 0), ('webpy/webpy', 0.5002906918525696, 'web', 0)]

56

5

null

3.04

84

52

34

0

22

493

22

84

156

90

1.9

58

1,013

llm

https://github.com/whitead/paper-qa

[]

null

[]

1

null

whitead/paper-qa

paper-qa

3,383

321

43

Python

null

LLM Chain for answering questions from documents with citations

whitead

2024-01-13

2023-02-05

51

65.963788

null

LLM Chain for answering questions from documents with citations

['chatgpt', 'nlp', 'question-answering']

2023-12-07

[('rlancemartin/auto-evaluator', 0.5889334678649902, 'llm', 1), ('princeton-nlp/alce', 0.5843133330345154, 'llm', 0), ('night-chen/toolqa', 0.54909348487854, 'llm', 1), ('explosion/spacy-llm', 0.5373473763465881, 'llm', 1), ('mooler0410/llmspracticalguide', 0.5275523066520691, 'study', 1), ('deepset-ai/haystack', 0.5140941143035889, 'llm', 3)]

12

4

null

3.31

33

17

11

1

75

83

75

33

22

90

0.7

58

1,528

llm

https://github.com/minimaxir/simpleaichat

[]

null

[]

null

minimaxir/simpleaichat

simpleaichat

3,227

210

34

Python

null

Python package for easily interfacing with chat apps, with robust features and minimal code complexity.

minimaxir

2024-01-12

2023-05-06

38

83.973978

null

Python package for easily interfacing with chat apps, with robust features and minimal code complexity.

['ai', 'chatgpt']

2024-01-08

[('embedchain/embedchain', 0.7047023773193359, 'llm', 2), ('run-llama/rags', 0.6775078177452087, 'llm', 1), ('togethercomputer/openchatkit', 0.6666284203529358, 'nlp', 0), ('killianlucas/open-interpreter', 0.6259564757347107, 'llm', 1), ('rcgai/simplyretrieve', 0.6199681162834167, 'llm', 0), ('cheshire-cat-ai/core', 0.613688588142395, 'llm', 1), ('prefecthq/marvin', 0.6048039197921753, 'nlp', 1), ('blinkdl/chatrwkv', 0.5946717262268066, 'llm', 1), ('rasahq/rasa', 0.5821955800056458, 'llm', 0), ('krohling/bondai', 0.5760908722877502, 'llm', 0), ('chatarena/chatarena', 0.5708586573600769, 'llm', 2), ('nomic-ai/gpt4all', 0.5681280493736267, 'llm', 0), ('chainlit/chainlit', 0.5655502080917358, 'llm', 1), ('willmcgugan/textual', 0.5615967512130737, 'term', 0), ('deeppavlov/deeppavlov', 0.559428870677948, 'nlp', 1), ('fasteval/fasteval', 0.559170663356781, 'llm', 0), ('microsoft/chatgpt-robot-manipulation-prompts', 0.5525240302085876, 'llm', 0), ('microsoft/autogen', 0.5520246028900146, 'llm', 1), ('openai/gpt-discord-bot', 0.552017331123352, 'llm', 0), ('larsbaunwall/bricky', 0.5494028925895691, 'llm', 1), ('openai/openai-cookbook', 0.5488078594207764, 'ml', 1), ('hoffstadt/dearpygui', 0.5460814237594604, 'gui', 0), ('nvidia/nemo', 0.5450947284698486, 'nlp', 0), ('xtekky/gpt4free', 0.5435710549354553, 'llm', 1), ('pathwaycom/llm-app', 0.5408278703689575, 'llm', 0), ('gunthercox/chatterbot', 0.5406122207641602, 'nlp', 0), ('uberi/speech_recognition', 0.5369465351104736, 'ml', 0), ('langchain-ai/chat-langchain', 0.5350149273872375, 'llm', 0), ('bhaskatripathi/pdfgpt', 0.5324260592460632, 'llm', 0), ('gventuri/pandas-ai', 0.5319541692733765, 'pandas', 1), ('openlmlab/moss', 0.5309569835662842, 'llm', 1), ('hwchase17/langchain', 0.5275580883026123, 'llm', 0), ('pndurette/gtts', 0.526296854019165, 'util', 0), ('lm-sys/fastchat', 0.526286244392395, 'llm', 0), ('masoniteframework/masonite', 0.5257116556167603, 'web', 0), ('mayooear/gpt4-pdf-chatbot-langchain', 0.5190370678901672, 'llm', 0), ('reloadware/reloadium', 0.509559154510498, 'profiling', 2), ('kalliope-project/kalliope', 0.5094994902610779, 'util', 0), ('minimaxir/aitextgen', 0.507713258266449, 'llm', 0), ('gunthercox/chatterbot-corpus', 0.5073516964912415, 'nlp', 0), ('eternnoir/pytelegrambotapi', 0.5022081732749939, 'util', 0), ('mnotgod96/appagent', 0.501400351524353, 'llm', 1)]

12

2

null

2.29

28

10

8

0

6

9

6

28

29

90

1

58

1,286

data

https://github.com/docarray/docarray

[]

null

[]

null

docarray/docarray

docarray

2,620

216

45

Python

https://docs.docarray.org/

Represent, send, store and search multimodal data

docarray

2024-01-14

2021-12-14

111

23.603604

https://avatars.githubusercontent.com/u/117445116?v=4

Represent, send, store and search multimodal data

['cross-modal', 'data-structures', 'dataclass', 'deep-learning', 'docarray', 'elasticsearch', 'fastapi', 'machine-learning', 'multi-modal', 'multimodal', 'nearest-neighbor-search', 'nested-data', 'neural-search', 'protobuf', 'pydantic', 'pytorch', 'qdrant', 'semantic-search', 'weaviate']

2024-01-02

[('milvus-io/bootcamp', 0.677416205406189, 'data', 1), ('next-gpt/next-gpt', 0.5986325144767761, 'llm', 1), ('thilinarajapakse/simpletransformers', 0.5803972482681274, 'nlp', 0), ('nomic-ai/nomic', 0.5800225734710693, 'nlp', 0), ('activeloopai/deeplake', 0.5793482661247253, 'ml-ops', 3), ('neuml/txtai', 0.5759537816047668, 'nlp', 3), ('marqo-ai/marqo', 0.5685033798217773, 'ml', 4), ('jina-ai/clip-as-service', 0.5395568609237671, 'nlp', 3), ('qdrant/qdrant', 0.5395107865333557, 'data', 3), ('freedmand/semantra', 0.5385406017303467, 'ml', 2), ('explosion/thinc', 0.5351216793060303, 'ml-dl', 3), ('jina-ai/jina', 0.5284995436668396, 'ml', 5), ('jina-ai/finetuner', 0.5270631313323975, 'ml', 1), ('lutzroeder/netron', 0.51971834897995, 'ml', 3), ('paddlepaddle/paddlenlp', 0.517856240272522, 'llm', 1), ('facebookresearch/mmf', 0.516020655632019, 'ml-dl', 3), ('gradio-app/gradio', 0.5143248438835144, 'viz', 2), ('huggingface/datasets', 0.511342465877533, 'nlp', 3), ('huggingface/autotrain-advanced', 0.5089057087898254, 'ml', 2), ('awslabs/autogluon', 0.5075685381889343, 'ml', 3), ('jina-ai/vectordb', 0.5065739154815674, 'data', 1), ('huggingface/transformers', 0.5064188241958618, 'nlp', 3), ('ddbourgin/numpy-ml', 0.5052067637443542, 'ml', 1), ('a-r-j/graphein', 0.5024240612983704, 'sim', 2), ('tensorlayer/tensorlayer', 0.5022443532943726, 'ml-rl', 1), ('intellabs/fastrag', 0.501563549041748, 'nlp', 2)]

72

2

null

8.4

35

21

25

0

17

81

17

35

124

90

3.5

58

1,358

gis

https://github.com/opengeos/segment-geospatial

[]

null

[]

null

opengeos/segment-geospatial

segment-geospatial

2,478

247

52

Python

https://samgeo.gishub.org

A Python package for segmenting geospatial data with the Segment Anything Model (SAM)

opengeos

2024-01-13

2023-04-19

40

60.65035

https://avatars.githubusercontent.com/u/129896036?v=4

A Python package for segmenting geospatial data with the Segment Anything Model (SAM)

['artificial-intelligence', 'deep-learning', 'geopython', 'geospatial', 'machine-learning', 'segment-anything', 'segmentation']

2023-12-07

[('earthlab/earthpy', 0.5494171977043152, 'gis', 0), ('sentinel-hub/eo-learn', 0.5391361117362976, 'gis', 1), ('geopandas/geopandas', 0.5388274788856506, 'gis', 1), ('microsoft/torchgeo', 0.5342783331871033, 'gis', 2), ('osgeo/grass', 0.5276463627815247, 'gis', 2), ('residentmario/geoplot', 0.5210736989974976, 'gis', 0), ('fatiando/verde', 0.5204988121986389, 'gis', 2), ('remotesensinglab/raster4ml', 0.5023316144943237, 'gis', 1)]

11

4

null

2.94

22

12

9

1

22

30

22

36

90

1.6

58

859

util

https://github.com/dosisod/refurb

[]

null

[]

1

null

dosisod/refurb

refurb

2,425

55

16

Python

null

A tool for refurbishing and modernizing Python codebases

dosisod

2024-01-10

2022-07-27

78

30.751812

null

A tool for refurbishing and modernizing Python codebases

['cli', 'gplv3', 'mypy', 'python310', 'testing']

2024-01-13

[('pypa/hatch', 0.6656979322433472, 'util', 1), ('facebookincubator/bowler', 0.5965598225593567, 'util', 0), ('pypa/pipenv', 0.5785287618637085, 'util', 0), ('rubik/radon', 0.5743918418884277, 'util', 1), ('prompt-toolkit/ptpython', 0.573533296585083, 'util', 1), ('python-rope/rope', 0.5674479007720947, 'util', 0), ('pypy/pypy', 0.5643258094787598, 'util', 0), ('pdm-project/pdm', 0.5603682398796082, 'util', 0), ('jendrikseipp/vulture', 0.5567197203636169, 'util', 0), ('google/jax', 0.5519415736198425, 'ml', 0), ('nedbat/coveragepy', 0.5513451099395752, 'testing', 0), ('pympler/pympler', 0.5501025915145874, 'perf', 0), ('indygreg/pyoxidizer', 0.5480595827102661, 'util', 0), ('amaargiru/pyroad', 0.5455231070518494, 'study', 0), ('sourcery-ai/sourcery', 0.5449427366256714, 'util', 0), ('pyston/pyston', 0.5432273149490356, 'util', 0), ('python/cpython', 0.5401459336280823, 'util', 0), ('microsoft/pycodegpt', 0.5347919464111328, 'llm', 0), ('hhatto/autopep8', 0.5332099795341492, 'util', 0), ('eleutherai/pyfra', 0.5314339399337769, 'ml', 0), ('google/gin-config', 0.5311492085456848, 'util', 0), ('exaloop/codon', 0.5304907560348511, 'perf', 0), ('pytoolz/toolz', 0.5235017538070679, 'util', 0), ('hadialqattan/pycln', 0.5226925611495972, 'util', 0), ('cython/cython', 0.5158920288085938, 'util', 0), ('psf/black', 0.514424204826355, 'util', 0), ('jazzband/pip-tools', 0.5137325525283813, 'util', 0), ('erotemic/ubelt', 0.513725996017456, 'util', 0), ('asottile/reorder-python-imports', 0.5132452249526978, 'util', 0), ('libtcod/python-tcod', 0.5105434060096741, 'gamedev', 0), ('google/yapf', 0.5096585154533386, 'util', 0), ('beeware/briefcase', 0.5095663666725159, 'util', 0), ('landscapeio/prospector', 0.5087876915931702, 'util', 0), ('eugeneyan/python-collab-template', 0.5078116059303284, 'template', 0), ('mkdocstrings/griffe', 0.5076294541358948, 'util', 0), ('samuelcolvin/python-devtools', 0.5065819621086121, 'debug', 0), ('pypa/virtualenv', 0.5063945055007935, 'util', 0), ('willmcgugan/textual', 0.5046628713607788, 'term', 1), ('dgilland/cacheout', 0.5029307007789612, 'perf', 0), ('pypi/warehouse', 0.5017030239105225, 'util', 0)]

16

7

null

2.67

33

28

18

0

20

25

20

33

61

90

1.8

58

1,809

data

https://github.com/lancedb/lancedb

['vectordb']

null

[]

null

lancedb/lancedb

lancedb

1,903

113

19

Python

https://lancedb.github.io/lancedb/

Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!

lancedb

2024-01-14

2023-02-28

48

39.645833

https://avatars.githubusercontent.com/u/108903835?v=4

Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!

['approximate-nearest-neighbor-search', 'image-search', 'nearest-neighbor-search', 'recommender-system', 'search-engine', 'semantic-search', 'similarity-search', 'vector-database']

['approximate-nearest-neighbor-search', 'image-search', 'nearest-neighbor-search', 'recommender-system', 'search-engine', 'semantic-search', 'similarity-search', 'vector-database', 'vectordb']

2024-01-14

[('activeloopai/deeplake', 0.7212356925010681, 'ml-ops', 1), ('qdrant/qdrant', 0.6593559384346008, 'data', 7), ('pathwaycom/llm-app', 0.6573936343193054, 'llm', 1), ('chroma-core/chroma', 0.6137559413909912, 'data', 1), ('jina-ai/vectordb', 0.612372100353241, 'data', 2), ('featureform/embeddinghub', 0.6071080565452576, 'nlp', 1), ('microsoft/semantic-kernel', 0.6036065220832825, 'llm', 0), ('alphasecio/langchain-examples', 0.601751446723938, 'llm', 1), ('superduperdb/superduperdb', 0.6009349226951599, 'data', 1), ('hegelai/prompttools', 0.5837177634239197, 'llm', 0), ('ludwig-ai/ludwig', 0.5785049796104431, 'ml-ops', 0), ('neuml/txtai', 0.574266254901886, 'nlp', 3), ('milvus-io/bootcamp', 0.566419780254364, 'data', 2), ('nebuly-ai/nebullvm', 0.5628674030303955, 'perf', 0), ('dgarnitz/vectorflow', 0.5619788765907288, 'data', 0), ('jerryjliu/llama_index', 0.5558105707168579, 'llm', 1), ('deepset-ai/haystack', 0.5541740655899048, 'llm', 1), ('qdrant/vector-db-benchmark', 0.5436363816261292, 'perf', 1), ('bigscience-workshop/petals', 0.5394517183303833, 'data', 0), ('microsoft/promptflow', 0.5394440293312073, 'llm', 0), ('mindsdb/mindsdb', 0.5393930077552795, 'data', 1), ('cheshire-cat-ai/core', 0.5356892347335815, 'llm', 0), ('tigerlab-ai/tiger', 0.531322181224823, 'llm', 0), ('zilliztech/gptcache', 0.5283774137496948, 'llm', 2), ('feast-dev/feast', 0.5253369808197021, 'ml-ops', 0), ('marqo-ai/marqo', 0.5243335366249084, 'ml', 2), ('llmware-ai/llmware', 0.5239478945732117, 'llm', 1), ('kagisearch/vectordb', 0.5210687518119812, 'data', 1), ('intel/intel-extension-for-transformers', 0.5155736207962036, 'perf', 0), ('paddlepaddle/paddlenlp', 0.5152085423469543, 'llm', 1), ('microsoft/torchscale', 0.5128360390663147, 'llm', 0), ('coleifer/peewee', 0.5083345770835876, 'data', 0), ('qdrant/fastembed', 0.507724940776825, 'ml', 1), ('vllm-project/vllm', 0.5034992694854736, 'llm', 0), ('run-llama/llama-hub', 0.5028201937675476, 'data', 0), ('ml-tooling/opyrator', 0.501854658126831, 'viz', 0)]

39

2

null

11.44

290

201

11

0

68

107

68

289

239

90

0.8

58

1,513

llm

https://github.com/neulab/prompt2model

['language-model', 'deployment']

null

[]

null

neulab/prompt2model

prompt2model

1,768

152

23

Python

null

prompt2model - Generate Deployable Models from Natural Language Instructions

neulab

2024-01-13

2023-03-27

44

40.05178

https://avatars.githubusercontent.com/u/22324665?v=4

prompt2model - Generate Deployable Models from Natural Language Instructions

[]

['deployment', 'language-model']

2024-01-12

[('hazyresearch/ama_prompting', 0.687862753868103, 'llm', 0), ('keirp/automatic_prompt_engineer', 0.6848369836807251, 'llm', 1), ('1rgs/jsonformer', 0.6683309674263, 'llm', 0), ('guidance-ai/guidance', 0.6568854451179504, 'llm', 1), ('ctlllll/llm-toolmaker', 0.623613178730011, 'llm', 1), ('promptslab/promptify', 0.5863036513328552, 'nlp', 0), ('srush/minichain', 0.5800988674163818, 'llm', 0), ('conceptofmind/toolformer', 0.5687054395675659, 'llm', 1), ('yizhongw/self-instruct', 0.5685259699821472, 'llm', 1), ('agenta-ai/agenta', 0.5488535761833191, 'llm', 0), ('ai21labs/lm-evaluation', 0.5453250408172607, 'llm', 1), ('juncongmoo/pyllama', 0.5409372448921204, 'llm', 0), ('reasoning-machines/pal', 0.5284048318862915, 'llm', 1), ('cg123/mergekit', 0.5275200009346008, 'llm', 0), ('thudm/codegeex', 0.525926411151886, 'llm', 0), ('hannibal046/awesome-llm', 0.525016188621521, 'study', 1), ('bigscience-workshop/promptsource', 0.5239977240562439, 'nlp', 0), ('facebookresearch/shepherd', 0.52313631772995, 'llm', 1), ('lianjiatech/belle', 0.5222576260566711, 'llm', 0), ('lm-sys/fastchat', 0.5152702331542969, 'llm', 1), ('microsoft/autogen', 0.5132074356079102, 'llm', 0), ('tatsu-lab/stanford_alpaca', 0.5068913102149963, 'llm', 1), ('defog-ai/sqlcoder', 0.5062905550003052, 'llm', 1)]

13

6

null

3.19

33

18

10

0

9

11

9

33

56

90

1.7

58

1,873

llm

https://github.com/llmware-ai/llmware

[]

null

[]

null

llmware-ai/llmware

llmware

1,744

141

29

Python

https://pypi.org/project/llmware/

Providing enterprise-grade LLM-based development framework, tools, and fine-tuned models.

llmware-ai

2024-01-14

2023-09-29

17

99.252033

https://avatars.githubusercontent.com/u/145479774?v=4

Providing enterprise-grade LLM-based development framework, tools, and fine-tuned models.

['ai', 'bert', 'embedding-vectors', 'embeddings', 'faiss', 'generative-ai', 'information-retrieval', 'large-language-models', 'machine-learning', 'milvus', 'nlp', 'parsing', 'pytorch', 'question-answering', 'rag', 'retrieval-augmented-generation', 'semantic-search', 'transformers']

2024-01-10

[('paddlepaddle/paddlenlp', 0.7560280561447144, 'llm', 4), ('neuml/txtai', 0.7031641602516174, 'nlp', 9), ('deepset-ai/haystack', 0.6901717185974121, 'llm', 11), ('intellabs/fastrag', 0.669150710105896, 'nlp', 6), ('explosion/spacy-llm', 0.6662053465843201, 'llm', 3), ('jina-ai/finetuner', 0.6378600597381592, 'ml', 1), ('night-chen/toolqa', 0.6234237551689148, 'llm', 2), ('argilla-io/argilla', 0.6205747723579407, 'nlp', 3), ('thilinarajapakse/simpletransformers', 0.6119190454483032, 'nlp', 2), ('deepset-ai/farm', 0.6115893721580505, 'nlp', 4), ('cheshire-cat-ai/core', 0.6055431962013245, 'llm', 1), ('mooler0410/llmspracticalguide', 0.6028851270675659, 'study', 2), ('hegelai/prompttools', 0.6007319092750549, 'llm', 3), ('nvidia/deeplearningexamples', 0.5966246128082275, 'ml-dl', 3), ('young-geng/easylm', 0.593721330165863, 'llm', 1), ('alibaba/easynlp', 0.592271625995636, 'nlp', 5), ('lm-sys/fastchat', 0.5916407704353333, 'llm', 0), ('ddangelov/top2vec', 0.5913721323013306, 'nlp', 2), ('microsoft/generative-ai-for-beginners', 0.5911704301834106, 'study', 4), ('rcgai/simplyretrieve', 0.5904434323310852, 'llm', 5), ('huggingface/transformers', 0.5898783206939697, 'nlp', 4), ('jonasgeiping/cramming', 0.5896017551422119, 'nlp', 1), ('eugeneyan/obsidian-copilot', 0.5871189832687378, 'llm', 3), ('nebuly-ai/nebullvm', 0.5862234830856323, 'perf', 2), ('jina-ai/clip-as-service', 0.5855153203010559, 'nlp', 2), ('extreme-bert/extreme-bert', 0.581847071647644, 'llm', 4), ('maartengr/bertopic', 0.5808184742927551, 'nlp', 4), ('confident-ai/deepeval', 0.5799471735954285, 'testing', 0), ('tigerlab-ai/tiger', 0.5777447819709778, 'llm', 2), ('pathwaycom/llm-app', 0.5754697322845459, 'llm', 3), ('lianjiatech/belle', 0.5731709003448486, 'llm', 0), ('chroma-core/chroma', 0.5633347034454346, 'data', 1), ('openbmb/toolbench', 0.5629839301109314, 'llm', 0), ('infinitylogesh/mutate', 0.5625592470169067, 'nlp', 0), ('arize-ai/phoenix', 0.5607779026031494, 'ml-interpretability', 0), ('graykode/nlp-tutorial', 0.559558093547821, 'study', 3), ('rasahq/rasa', 0.5576108694076538, 'llm', 2), ('microsoft/lmops', 0.5573378205299377, 'llm', 1), ('mindsdb/mindsdb', 0.55570387840271, 'data', 3), ('eleutherai/the-pile', 0.5548039078712463, 'data', 0), ('explosion/spacy', 0.5547406077384949, 'nlp', 3), ('explosion/thinc', 0.5531507730484009, 'ml-dl', 4), ('explosion/spacy-models', 0.5522136092185974, 'nlp', 2), ('ludwig-ai/ludwig', 0.5516101717948914, 'ml-ops', 2), ('lucidrains/toolformer-pytorch', 0.5493955016136169, 'llm', 1), ('plasticityai/magnitude', 0.5475419759750366, 'nlp', 3), ('salesforce/xgen', 0.5470395684242249, 'llm', 2), ('deeppavlov/deeppavlov', 0.5467641353607178, 'nlp', 4), ('bentoml/bentoml', 0.5451672673225403, 'ml-ops', 3), ('databrickslabs/dolly', 0.5424628257751465, 'llm', 0), ('flairnlp/flair', 0.5408936738967896, 'nlp', 3), ('huggingface/text-generation-inference', 0.5404112339019775, 'llm', 2), ('mlc-ai/mlc-llm', 0.5390260815620422, 'llm', 0), ('jina-ai/vectordb', 0.5389397740364075, 'data', 0), ('muennighoff/sgpt', 0.5382522940635681, 'llm', 3), ('srush/minichain', 0.5373873114585876, 'llm', 1), ('bigscience-workshop/petals', 0.5363177061080933, 'data', 4), ('openlmlab/moss', 0.5356535911560059, 'llm', 1), ('amansrivastava17/embedding-as-service', 0.5347151756286621, 'nlp', 4), ('salesforce/codet5', 0.5333616733551025, 'nlp', 1), ('keras-team/keras-nlp', 0.5331376194953918, 'nlp', 2), ('ai21labs/lm-evaluation', 0.5320602655410767, 'llm', 0), ('allenai/allennlp', 0.5309963226318359, 'nlp', 2), ('microsoft/promptflow', 0.5309350490570068, 'llm', 1), ('tatsu-lab/stanford_alpaca', 0.5306206345558167, 'llm', 0), ('stanfordnlp/dspy', 0.5297998785972595, 'llm', 0), ('dylanhogg/llmgraph', 0.5296906232833862, 'ml', 0), ('activeloopai/deeplake', 0.529674768447876, 'ml-ops', 4), ('juncongmoo/pyllama', 0.5293798446655273, 'llm', 0), ('hiyouga/llama-factory', 0.5291882157325745, 'llm', 3), ('hiyouga/llama-efficient-tuning', 0.5291881561279297, 'llm', 3), ('explosion/spacy-transformers', 0.5283253192901611, 'llm', 4), ('lupantech/chameleon-llm', 0.5269300937652588, 'llm', 1), ('reasoning-machines/pal', 0.5255475640296936, 'llm', 1), ('qdrant/fastembed', 0.5254819989204407, 'ml', 3), ('chancefocus/pixiu', 0.5248722434043884, 'finance', 4), ('nomic-ai/gpt4all', 0.5244438648223877, 'llm', 0), ('lancedb/lancedb', 0.5239478945732117, 'data', 1), ('optimalscale/lmflow', 0.5209429264068604, 'llm', 1), ('ctlllll/llm-toolmaker', 0.5208345055580139, 'llm', 0), ('norskregnesentral/skweak', 0.5207846760749817, 'nlp', 0), ('embedchain/embedchain', 0.5193879008293152, 'llm', 1), ('microsoft/unilm', 0.5189810991287231, 'nlp', 1), ('milvus-io/bootcamp', 0.518172025680542, 'data', 4), ('huggingface/text-embeddings-inference', 0.517711341381073, 'llm', 2), ('microsoft/autogen', 0.5167933702468872, 'llm', 0), ('yueyu1030/attrprompt', 0.5132665038108826, 'llm', 1), ('koaning/embetter', 0.5121687650680542, 'data', 0), ('bigscience-workshop/megatron-deepspeed', 0.5115044116973877, 'llm', 0), ('microsoft/megatron-deepspeed', 0.5115044116973877, 'llm', 0), ('nltk/nltk', 0.5111628770828247, 'nlp', 2), ('paddlepaddle/rocketqa', 0.510935366153717, 'nlp', 3), ('iryna-kondr/scikit-llm', 0.5102970600128174, 'llm', 2), ('giskard-ai/giskard', 0.5087332725524902, 'data', 1), ('qanastek/drbert', 0.5081828832626343, 'llm', 3), ('freedomintelligence/llmzoo', 0.5058205127716064, 'llm', 0), ('hannibal046/awesome-llm', 0.5052445530891418, 'study', 0), ('kagisearch/vectordb', 0.5052314400672913, 'data', 2), ('microsoft/torchscale', 0.5042523741722107, 'llm', 1), ('bobazooba/xllm', 0.503739595413208, 'llm', 2), ('google-research/electra', 0.5037044882774353, 'ml-dl', 1), ('nvidia/nemo', 0.503142237663269, 'nlp', 1), ('ofa-sys/ofa', 0.5022109150886536, 'llm', 0), ('huggingface/datasets', 0.5021990537643433, 'nlp', 3), ('makcedward/nlpaug', 0.5014007091522217, 'nlp', 3), ('koaning/whatlies', 0.501112163066864, 'nlp', 2)]

13

3

null

4.31

229

205

4

0

229

138

90

0.6

58

1,267

perf

https://github.com/intel/intel-extension-for-transformers

[]

null

[]

null

intel/intel-extension-for-transformers

intel-extension-for-transformers

1,672

166

25

C++

null

⚡ Build your chatbot within minutes on your favorite device; offer SOTA compression techniques for LLMs; run LLMs efficiently on Intel Platforms⚡

intel

2024-01-14

2022-11-11

63

26.301124

https://avatars.githubusercontent.com/u/17888862?v=4

⚡ Build your chatbot within minutes on your favorite device; offer SOTA compression techniques for LLMs; run LLMs efficiently on Intel Platforms⚡

['4-bits', 'attention-sink', 'chatbot', 'chatpdf', 'cpu', 'gaudi2', 'gpu', 'habana', 'intel-optimized-llamacpp', 'large-language-model', 'llm-cpu', 'llm-inference', 'neural-chat', 'neural-chat-7b', 'neurips2023', 'pc', 'speculative-decoding', 'streamingllm', 'xeon']

2024-01-13

[('bigscience-workshop/petals', 0.7305524945259094, 'data', 1), ('nomic-ai/gpt4all', 0.7130550742149353, 'llm', 2), ('h2oai/h2o-llmstudio', 0.6861023902893066, 'llm', 1), ('pathwaycom/llm-app', 0.6731693148612976, 'llm', 1), ('deep-diver/llm-as-chatbot', 0.6634297966957092, 'llm', 1), ('hwchase17/langchain', 0.662899911403656, 'llm', 1), ('microsoft/promptflow', 0.6592389345169067, 'llm', 0), ('bobazooba/xllm', 0.6433131694793701, 'llm', 0), ('deepset-ai/haystack', 0.6430325508117676, 'llm', 0), ('zilliztech/gptcache', 0.6376039981842041, 'llm', 1), ('microsoft/semantic-kernel', 0.6336042284965515, 'llm', 0), ('run-llama/rags', 0.6312287449836731, 'llm', 1), ('microsoft/autogen', 0.6164318323135376, 'llm', 2), ('microsoft/llmlingua', 0.6135388016700745, 'llm', 0), ('embedchain/embedchain', 0.6132449507713318, 'llm', 0), ('hiyouga/llama-efficient-tuning', 0.608906626701355, 'llm', 0), ('hiyouga/llama-factory', 0.6089065670967102, 'llm', 0), ('li-plus/chatglm.cpp', 0.6037748456001282, 'llm', 0), ('thudm/chatglm2-6b', 0.6007229685783386, 'llm', 0), ('vllm-project/vllm', 0.5956281423568726, 'llm', 0), ('fasteval/fasteval', 0.5938782095909119, 'llm', 0), ('bentoml/openllm', 0.5912082195281982, 'ml-ops', 1), ('predibase/lorax', 0.5878379940986633, 'llm', 2), ('young-geng/easylm', 0.5872876048088074, 'llm', 1), ('mlc-ai/web-llm', 0.5826047658920288, 'llm', 0), ('chainlit/chainlit', 0.5824191570281982, 'llm', 0), ('iryna-kondr/scikit-llm', 0.5800312757492065, 'llm', 0), ('salesforce/xgen', 0.5792416334152222, 'llm', 0), ('shishirpatil/gorilla', 0.5774163603782654, 'llm', 0), ('mmabrouk/chatgpt-wrapper', 0.5764015913009644, 'llm', 1), ('tigerlab-ai/tiger', 0.5748347640037537, 'llm', 0), ('lightning-ai/lit-gpt', 0.5745608806610107, 'llm', 0), ('nebuly-ai/nebullvm', 0.5715976357460022, 'perf', 0), ('rcgai/simplyretrieve', 0.5712392330169678, 'llm', 0), ('microsoft/torchscale', 0.570101261138916, 'llm', 0), ('microsoft/promptcraft-robotics', 0.5677699446678162, 'sim', 0), ('paddlepaddle/paddlenlp', 0.5665012001991272, 'llm', 0), ('run-llama/llama-hub', 0.5623946189880371, 'data', 0), ('alpha-vllm/llama2-accessory', 0.5544970035552979, 'llm', 0), ('dylanhogg/llmgraph', 0.5522487163543701, 'ml', 1), ('lightning-ai/lit-llama', 0.5519506335258484, 'llm', 0), ('confident-ai/deepeval', 0.5511168241500854, 'testing', 0), ('chatarena/chatarena', 0.5510158538818359, 'llm', 0), ('eugeneyan/open-llms', 0.5479944944381714, 'study', 0), ('ludwig-ai/ludwig', 0.5449299216270447, 'ml-ops', 0), ('cheshire-cat-ai/core', 0.5444093346595764, 'llm', 1), ('next-gpt/next-gpt', 0.5425037145614624, 'llm', 0), ('agenta-ai/agenta', 0.5398895144462585, 'llm', 0), ('nat/openplayground', 0.5346694588661194, 'llm', 0), ('mlc-ai/mlc-llm', 0.5288311243057251, 'llm', 0), ('salesforce/codet5', 0.5260124802589417, 'nlp', 0), ('jzhang38/tinyllama', 0.5206746459007263, 'llm', 0), ('titanml/takeoff', 0.5163436532020569, 'llm', 0), ('ray-project/ray-llm', 0.5162841081619263, 'llm', 1), ('haotian-liu/llava', 0.5162800550460815, 'llm', 1), ('lancedb/lancedb', 0.5155736207962036, 'data', 0), ('microsoft/jarvis', 0.5154780149459839, 'llm', 0), ('prefecthq/marvin', 0.5106049180030823, 'nlp', 0), ('lm-sys/fastchat', 0.5099033117294312, 'llm', 1), ('xtekky/gpt4free', 0.5091184973716736, 'llm', 1), ('mnotgod96/appagent', 0.5081307888031006, 'llm', 0), ('artidoro/qlora', 0.5075502395629883, 'llm', 0), ('mooler0410/llmspracticalguide', 0.5048488974571228, 'study', 0), ('microsoft/lmops', 0.5034509301185608, 'llm', 0), ('tloen/alpaca-lora', 0.5027761459350586, 'llm', 0), ('explosion/spacy-llm', 0.5016040205955505, 'llm', 0), ('argilla-io/argilla', 0.5005181431770325, 'nlp', 0), ('aws-samples/serverless-pdf-chat', 0.5002910494804382, 'llm', 0)]

91

2

null

24.88

702

650

14

0

8

15

8

702

760

90

1.1

58

1,760

term

https://github.com/tconbeer/harlequin

['tool', 'sql', 'data']

null

[]

1

null

tconbeer/harlequin

harlequin

1,637

30

12

Python

https://harlequin.sh

The SQL IDE for Your Terminal.

tconbeer

2024-01-14

2023-05-02

39

41.974359

null

The SQL IDE for Your Terminal.

[]

['data', 'sql', 'tool']

2024-01-12

[('tconbeer/sqlfmt', 0.569164514541626, 'data', 1), ('tiangolo/sqlmodel', 0.569147527217865, 'data', 1), ('sqlalchemy/sqlalchemy', 0.5578516721725464, 'data', 1), ('simonw/sqlite-utils', 0.5377789735794067, 'data', 0), ('saulpw/visidata', 0.5237422585487366, 'term', 0), ('methexis-inc/terminal-copilot', 0.5151594877243042, 'util', 0), ('ibis-project/ibis', 0.5111363530158997, 'data', 1)]

8

6

null

4.44

131

112

9

0

50

68

50

131

88

90

0.7

58

1,123

ml-rl

https://github.com/pytorch/rl

['reinforcement-learning']

null

[]

null

pytorch/rl

rl

1,621

212

40

Python

https://pytorch.org/rl

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

pytorch

2024-01-13

2022-02-01

104

15.586538

https://avatars.githubusercontent.com/u/21003710?v=4

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

['ai', 'control', 'decision-making', 'distributed-computing', 'machine-learning', 'marl', 'model-based-reinforcement-learning', 'multi-agent-reinforcement-learning', 'pytorch', 'reinforcement-learning', 'rl', 'robotics', 'torch']

2024-01-14

[('thu-ml/tianshou', 0.7527033090591431, 'ml-rl', 2), ('denys88/rl_games', 0.7474822402000427, 'ml-rl', 2), ('tensorlayer/tensorlayer', 0.7300659418106079, 'ml-rl', 1), ('humancompatibleai/imitation', 0.6811489462852478, 'ml-rl', 0), ('deepmind/acme', 0.6701556444168091, 'ml-rl', 1), ('pytorch/ignite', 0.6654600501060486, 'ml-dl', 2), ('google/dopamine', 0.6595585942268372, 'ml-rl', 2), ('shangtongzhang/reinforcement-learning-an-introduction', 0.6356885433197021, 'study', 1), ('skorch-dev/skorch', 0.6245636940002441, 'ml-dl', 2), ('facebookresearch/habitat-lab', 0.6235378384590149, 'sim', 3), ('unity-technologies/ml-agents', 0.6213619709014893, 'ml-rl', 2), ('keras-rl/keras-rl', 0.6202392578125, 'ml-rl', 2), ('pettingzoo-team/pettingzoo', 0.6150112748146057, 'ml-rl', 2), ('mrdbourke/pytorch-deep-learning', 0.6149892210960388, 'study', 2), ('arise-initiative/robosuite', 0.6132838129997253, 'ml-rl', 2), ('farama-foundation/gymnasium', 0.6115036010742188, 'ml-rl', 1), ('salesforce/warp-drive', 0.6080675721168518, 'ml-rl', 2), ('intel/intel-extension-for-pytorch', 0.6046189069747925, 'perf', 2), ('ai4finance-foundation/finrl', 0.5981391072273254, 'finance', 1), ('google/trax', 0.5977087020874023, 'ml-dl', 2), ('karpathy/micrograd', 0.5971662402153015, 'study', 0), ('openai/gym', 0.5818626880645752, 'ml-rl', 1), ('huggingface/transformers', 0.5793347954750061, 'nlp', 2), ('pyg-team/pytorch_geometric', 0.5780683755874634, 'ml-dl', 1), ('rasbt/machine-learning-book', 0.5708683729171753, 'study', 2), ('explosion/thinc', 0.5706343650817871, 'ml-dl', 3), ('allenai/allennlp', 0.5637892484664917, 'nlp', 1), ('ray-project/ray', 0.5598548054695129, 'ml-ops', 3), ('nvidia/apex', 0.552091121673584, 'ml-dl', 0), ('lightly-ai/lightly', 0.5465163588523865, 'ml', 2), ('openai/baselines', 0.5460628867149353, 'ml-rl', 0), ('pyro-ppl/pyro', 0.5450016856193542, 'ml-dl', 2), ('nvidia-omniverse/omniisaacgymenvs', 0.5446157455444336, 'sim', 0), ('kornia/kornia', 0.5435752272605896, 'ml-dl', 3), ('kzl/decision-transformer', 0.5421603322029114, 'ml-rl', 0), ('tensorflow/tensor2tensor', 0.539577305316925, 'ml', 2), ('determined-ai/determined', 0.5359745025634766, 'ml-ops', 2), ('projectmesa/mesa', 0.5338829159736633, 'sim', 0), ('facebookresearch/theseus', 0.5316617488861084, 'math', 2), ('nvidia-omniverse/orbit', 0.5298061966896057, 'sim', 1), ('merantix-momentum/squirrel-core', 0.527829647064209, 'ml', 3), ('pytorch/data', 0.5270489454269409, 'data', 0), ('ddbourgin/numpy-ml', 0.5264372229576111, 'ml', 2), ('keras-team/keras', 0.5254106521606445, 'ml-dl', 2), ('ashleve/lightning-hydra-template', 0.5253444314002991, 'util', 1), ('aws/sagemaker-python-sdk', 0.5228525996208191, 'ml', 2), ('inspirai/timechamber', 0.5206745862960815, 'sim', 1), ('lukaszahradnik/pyneuralogic', 0.5153552889823914, 'math', 2), ('probml/pyprobml', 0.514581561088562, 'ml', 2), ('pytorch/captum', 0.5139393210411072, 'ml-interpretability', 0), ('xl0/lovely-tensors', 0.5124273896217346, 'ml-dl', 1), ('intellabs/bayesian-torch', 0.5093467831611633, 'ml', 1), ('tensorflow/tensorflow', 0.508491039276123, 'ml-dl', 1), ('deepmind/dm_control', 0.507379412651062, 'ml-rl', 2), ('operand/agency', 0.5073025822639465, 'llm', 2), ('mlflow/mlflow', 0.5072483420372009, 'ml-ops', 2), ('bulletphysics/bullet3', 0.505810022354126, 'sim', 2), ('huggingface/huggingface_hub', 0.5057786703109741, 'ml', 2), ('google/tf-quant-finance', 0.5055859088897705, 'finance', 0), ('d2l-ai/d2l-en', 0.5053571462631226, 'study', 3), ('facebookresearch/pytorch3d', 0.5044132471084595, 'ml-dl', 0), ('huggingface/accelerate', 0.5024619102478027, 'ml', 0), ('facebookresearch/reagent', 0.5019720196723938, 'ml-rl', 0), ('ggerganov/ggml', 0.5019291043281555, 'ml', 1), ('horovod/horovod', 0.5009804368019104, 'ml-ops', 2)]

130

4

null

11.87

212

172

24

0

8

7

8

212

568

90

2.7

58

193

template

https://github.com/tiangolo/full-stack-fastapi-postgresql

[]

null

[]

null

tiangolo/full-stack-fastapi-postgresql

full-stack-fastapi-postgresql

14,174

2,531

249

TypeScript

null

Full stack, modern web application generator. Using FastAPI, PostgreSQL as database, Docker, automatic HTTPS and more.

tiangolo

2024-01-14

2019-02-23

257

55.059933

null

Full stack, modern web application generator. Using FastAPI, PostgreSQL as database, Docker, automatic HTTPS and more.

['backend', 'celery', 'cookiecutter', 'docker', 'fastapi', 'frontend', 'json', 'json-schema', 'jwt', 'letsencrypt', 'openapi', 'openapi3', 'pgadmin', 'postgresql', 'swagger', 'traefik', 'vue', 'vuex']

2023-12-27

[('tiangolo/fastapi', 0.6879447102546692, 'web', 6), ('piccolo-orm/piccolo_admin', 0.6423637866973877, 'data', 2), ('vitalik/django-ninja', 0.6353817582130432, 'web', 2), ('rawheel/fastapi-boilerplate', 0.6298112869262695, 'web', 3), ('aeternalis-ingenium/fastapi-backend-template', 0.6168069839477539, 'web', 4), ('hugapi/hug', 0.5920613408088684, 'util', 0), ('starlite-api/starlite', 0.5915384292602539, 'web', 2), ('python-restx/flask-restx', 0.5876633524894714, 'web', 2), ('simonw/datasette', 0.5789318084716797, 'data', 2), ('huge-success/sanic', 0.5729467868804932, 'web', 0), ('airbytehq/airbyte', 0.5710554718971252, 'data', 1), ('zenodo/zenodo', 0.5640177726745605, 'util', 1), ('awtkns/fastapi-crudrouter', 0.5604096055030823, 'web', 2), ('prefecthq/server', 0.5580776333808899, 'util', 0), ('orchest/orchest', 0.5576450228691101, 'ml-ops', 1), ('asacristani/fastapi-rocket-boilerplate', 0.5566263198852539, 'template', 1), ('s3rius/fastapi-template', 0.5562103986740112, 'web', 2), ('coleifer/peewee', 0.5561289191246033, 'data', 0), ('alphasecio/langchain-examples', 0.5519778728485107, 'llm', 0), ('willmcgugan/textual', 0.5517593026161194, 'term', 0), ('falconry/falcon', 0.5487000942230225, 'web', 0), ('dmontagu/fastapi_client', 0.5413647890090942, 'web', 0), ('buuntu/fastapi-react', 0.5327474474906921, 'template', 4), ('avaiga/taipy', 0.5292978286743164, 'data', 0), ('tiangolo/sqlmodel', 0.5256924629211426, 'data', 3), ('shishirpatil/gorilla', 0.5247654914855957, 'llm', 0), ('ajndkr/lanarky', 0.5205399394035339, 'llm', 1), ('pallets/werkzeug', 0.520187497138977, 'web', 0), ('gefyrahq/gefyra', 0.5177972912788391, 'util', 1), ('pallets/flask', 0.5168726444244385, 'web', 0), ('flet-dev/flet', 0.5064703822135925, 'web', 0), ('flyteorg/flyte', 0.5061784386634827, 'ml-ops', 0), ('pyeve/eve', 0.5053060054779053, 'web', 0), ('kestra-io/kestra', 0.501535952091217, 'ml-ops', 0), ('plotly/dash', 0.5003242492675781, 'viz', 0)]

21

4

null

0.52

63

36

60

1

0

1

63

79

90

1.3

57

1,716

util

https://github.com/google/yapf

['code-quality']

null

[]

null

google/yapf

yapf

13,543

958

214

Python

null

A formatter for Python files

google

2024-01-14

2015-03-18

462

29.259568

https://avatars.githubusercontent.com/u/1342004?v=4

A formatter for Python files

['formatter', 'google']

['code-quality', 'formatter', 'google']

2023-11-08

[('grantjenks/blue', 0.749129056930542, 'util', 2), ('hhatto/autopep8', 0.7038267850875854, 'util', 1), ('psf/black', 0.6890390515327454, 'util', 2), ('danielnoord/pydocstringformatter', 0.6070597171783447, 'util', 1), ('astral-sh/ruff', 0.6007269024848938, 'util', 1), ('pycqa/isort', 0.5961623191833496, 'util', 2), ('google/latexify_py', 0.5899499654769897, 'util', 0), ('landscapeio/prospector', 0.5676681995391846, 'util', 0), ('google/pytype', 0.5599178075790405, 'typing', 1), ('pygments/pygments', 0.5552298426628113, 'util', 0), ('python-markdown/markdown', 0.5518056154251099, 'util', 0), ('pycqa/flake8', 0.5436343550682068, 'util', 1), ('rubik/radon', 0.5423753261566162, 'util', 0), ('jendrikseipp/vulture', 0.5393766164779663, 'util', 1), ('pycqa/pyflakes', 0.5379751920700073, 'util', 0), ('nedbat/coveragepy', 0.535642147064209, 'testing', 0), ('imageio/imageio', 0.5354976654052734, 'util', 0), ('pytoolz/toolz', 0.5353810787200928, 'util', 0), ('agronholm/typeguard', 0.5313608050346375, 'typing', 1), ('microsoft/pyright', 0.5311009287834167, 'typing', 1), ('hadialqattan/pycln', 0.5293893218040466, 'util', 0), ('connorferster/handcalcs', 0.5293661952018738, 'jupyter', 0), ('willmcgugan/rich', 0.5237478017807007, 'term', 0), ('dask/fastparquet', 0.5155162811279297, 'data', 0), ('fsspec/filesystem_spec', 0.5129982233047485, 'util', 0), ('instagram/monkeytype', 0.5119272470474243, 'typing', 1), ('dosisod/refurb', 0.5096585154533386, 'util', 0), ('mynameisfiber/high_performance_python_2e', 0.5080813765525818, 'study', 0), ('pyutils/line_profiler', 0.5072764158248901, 'profiling', 0), ('pyfpdf/fpdf2', 0.5062951445579529, 'util', 0), ('pyston/pyston', 0.5001851320266724, 'util', 0)]

151

4

null

2.19

39

14

107

2

0

8

39

46

90

1.2

57

1,045

nlp

https://github.com/jina-ai/clip-as-service

[]

null

[]

null

jina-ai/clip-as-service

clip-as-service

12,043

2,056

217

Python

https://clip-as-service.jina.ai

🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP

jina-ai

2024-01-13

2018-11-12

272

44.252493

https://avatars.githubusercontent.com/u/60539444?v=4

🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP

['bert', 'bert-as-service', 'clip-as-service', 'clip-model', 'cross-modal-retrieval', 'cross-modality', 'deep-learning', 'image2vec', 'multi-modality', 'neural-search', 'onnx', 'openai', 'pytorch', 'sentence-encoding', 'sentence2vec']

2023-12-20

[('jina-ai/finetuner', 0.7554095387458801, 'ml', 2), ('ukplab/sentence-transformers', 0.7321420311927795, 'nlp', 0), ('rom1504/clip-retrieval', 0.6420944929122925, 'ml', 1), ('amansrivastava17/embedding-as-service', 0.6331066489219666, 'nlp', 4), ('openai/clip', 0.6114118695259094, 'ml-dl', 1), ('alibaba/easynlp', 0.6006197333335876, 'nlp', 3), ('paddlepaddle/paddlenlp', 0.5931671261787415, 'llm', 2), ('ddangelov/top2vec', 0.5902553796768188, 'nlp', 1), ('llmware-ai/llmware', 0.5855153203010559, 'llm', 2), ('qdrant/fastembed', 0.584290087223053, 'ml', 1), ('neuml/txtai', 0.5824137330055237, 'nlp', 1), ('extreme-bert/extreme-bert', 0.5639864802360535, 'llm', 3), ('plasticityai/magnitude', 0.5636166334152222, 'nlp', 0), ('intellabs/fastrag', 0.561098039150238, 'nlp', 0), ('nomic-ai/nomic', 0.5556612610816956, 'nlp', 0), ('koaning/whatlies', 0.553788423538208, 'nlp', 0), ('graykode/nlp-tutorial', 0.5440134406089783, 'study', 2), ('chroma-core/chroma', 0.5438365340232849, 'data', 0), ('deepset-ai/farm', 0.5426168441772461, 'nlp', 3), ('muennighoff/sgpt', 0.5414046049118042, 'llm', 1), ('huggingface/transformers', 0.540093183517456, 'nlp', 3), ('docarray/docarray', 0.5395568609237671, 'data', 3), ('lucidrains/imagen-pytorch', 0.5368449091911316, 'ml-dl', 1), ('koaning/embetter', 0.5349407196044922, 'data', 0), ('nvidia/deeplearningexamples', 0.5337973833084106, 'ml-dl', 2), ('jina-ai/vectordb', 0.5312561988830566, 'data', 1), ('facebookresearch/mmf', 0.52168208360672, 'ml-dl', 2), ('explosion/thinc', 0.5208788514137268, 'ml-dl', 2), ('nvlabs/prismer', 0.5206122994422913, 'diffusion', 0), ('milvus-io/bootcamp', 0.5121859312057495, 'data', 1), ('maartengr/bertopic', 0.5079023838043213, 'nlp', 1), ('paddlepaddle/rocketqa', 0.506847620010376, 'nlp', 0), ('deeppavlov/deeppavlov', 0.5053911805152893, 'nlp', 1), ('luodian/otter', 0.5049297213554382, 'llm', 2), ('ofa-sys/ofa', 0.5020403265953064, 'llm', 0), ('huggingface/text-embeddings-inference', 0.5006672143936157, 'llm', 0)]

66

4

null

0.31

16

7

63

1

2

24

2

16

32

90

2

57

598

ml

https://github.com/cleanlab/cleanlab

[]

null

[]

null

cleanlab/cleanlab

cleanlab

7,697

619

79

Python

https://cleanlab.ai

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

cleanlab

2024-01-13

2018-05-11

298

25.779426

https://avatars.githubusercontent.com/u/90712480?v=4

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

['active-learning', 'annotation', 'data-analysis', 'data-centric-ai', 'data-cleaning', 'data-curation', 'data-labeling', 'data-profiling', 'data-quality', 'data-science', 'data-validation', 'dataops', 'dataquality', 'datasets', 'labeling', 'llms', 'noisy-labels', 'out-of-distribution-detection', 'outlier-detection', 'weak-supervision']

2024-01-12

[('ydataai/ydata-quality', 0.583878219127655, 'data', 0), ('whylabs/whylogs', 0.5660983324050903, 'util', 3), ('doccano/doccano', 0.5571958422660828, 'nlp', 2), ('csinva/imodels', 0.5562312602996826, 'ml', 1), ('netflix/metaflow', 0.5494846105575562, 'ml-ops', 1), ('alirezadir/machine-learning-interview-enlightener', 0.5334048867225647, 'study', 0), ('koaning/embetter', 0.5257184505462646, 'data', 1), ('argilla-io/argilla', 0.5151708722114563, 'nlp', 2), ('bentoml/bentoml', 0.5148969292640686, 'ml-ops', 0), ('koaning/bulk', 0.5123386383056641, 'data', 1), ('polyaxon/datatile', 0.5088824033737183, 'pandas', 4), ('makcedward/nlpaug', 0.505994439125061, 'nlp', 1), ('mlflow/mlflow', 0.5033455491065979, 'ml-ops', 0)]

44

3

null

5.56

135

69

0

4

2

4

135

157

90

1.2

57

552

ml-dl

https://github.com/arogozhnikov/einops

[]

null

[]

null

arogozhnikov/einops

einops

7,548

328

69

Python

https://einops.rocks

Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

arogozhnikov

2024-01-13

2018-09-22

279

27.01227

null

Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

['chainer', 'cupy', 'deep-learning', 'einops', 'jax', 'keras', 'numpy', 'pytorch', 'tensor', 'tensorflow']

2024-01-11

[('tensorly/tensorly', 0.7486700415611267, 'ml-dl', 6), ('ggerganov/ggml', 0.674818754196167, 'ml', 0), ('intel/intel-extension-for-pytorch', 0.6702998876571655, 'perf', 2), ('rafiqhasan/auto-tensorflow', 0.6536889672279358, 'ml-dl', 1), ('huggingface/transformers', 0.6441165804862976, 'nlp', 4), ('patrick-kidger/torchtyping', 0.6377165913581848, 'typing', 1), ('tensorflow/addons', 0.6348954439163208, 'ml', 2), ('pytorch/ignite', 0.6346755027770996, 'ml-dl', 2), ('xl0/lovely-tensors', 0.6286166310310364, 'ml-dl', 2), ('pytorch/pytorch', 0.624183177947998, 'ml-dl', 3), ('nvidia/apex', 0.6182481646537781, 'ml-dl', 0), ('horovod/horovod', 0.6111495494842529, 'ml-ops', 4), ('google/tf-quant-finance', 0.6102033853530884, 'finance', 1), ('tlkh/tf-metal-experiments', 0.6099873781204224, 'perf', 2), ('karpathy/micrograd', 0.600235104560852, 'study', 0), ('skorch-dev/skorch', 0.599236786365509, 'ml-dl', 1), ('tensorflow/similarity', 0.5858622193336487, 'ml-dl', 2), ('rentruewang/koila', 0.5856212973594666, 'ml', 2), ('explosion/thinc', 0.5852126479148865, 'ml-dl', 4), ('google/gin-config', 0.5846500396728516, 'util', 1), ('keras-team/keras', 0.580649197101593, 'ml-dl', 4), ('tensorflow/mesh', 0.5747230052947998, 'ml-dl', 0), ('nvidia/tensorrt-llm', 0.5731545686721802, 'viz', 0), ('nvidia/deeplearningexamples', 0.5647768378257751, 'ml-dl', 3), ('keras-team/keras-nlp', 0.5635877251625061, 'nlp', 3), ('huggingface/accelerate', 0.5633874535560608, 'ml', 0), ('rasbt/machine-learning-book', 0.5617372989654541, 'study', 2), ('mrdbourke/m1-machine-learning-test', 0.556743323802948, 'ml', 1), ('nyandwi/modernconvnets', 0.5543664693832397, 'ml-dl', 2), ('huggingface/exporters', 0.5518941283226013, 'ml', 3), ('google/jax', 0.5517240762710571, 'ml', 2), ('ashleve/lightning-hydra-template', 0.5508671998977661, 'util', 2), ('cupy/cupy', 0.5499424934387207, 'math', 3), ('blackhc/toma', 0.5450114011764526, 'ml-dl', 1), ('fchollet/deep-learning-with-python-notebooks', 0.5417112112045288, 'study', 0), ('neuralmagic/sparseml', 0.5392698645591736, 'ml-dl', 3), ('ageron/handson-ml2', 0.5353853702545166, 'ml', 0), ('facebookresearch/pytorch3d', 0.5348989963531494, 'ml-dl', 0), ('pytorch/data', 0.5333592891693115, 'data', 0), ('google/trax', 0.5327727198600769, 'ml-dl', 3), ('mrdbourke/pytorch-deep-learning', 0.528740644454956, 'study', 2), ('pypy/pypy', 0.5274959206581116, 'util', 0), ('pytorch/captum', 0.524075984954834, 'ml-interpretability', 0), ('pytoolz/toolz', 0.5189169645309448, 'util', 0), ('tensorflow/tensorflow', 0.515922486782074, 'ml-dl', 2), ('ddbourgin/numpy-ml', 0.5156410336494446, 'ml', 0), ('deepmind/dm-haiku', 0.5126287341117859, 'ml-dl', 2), ('microsoft/onnxruntime', 0.5109891295433044, 'ml', 3), ('pyg-team/pytorch_geometric', 0.5090392231941223, 'ml-dl', 2), ('onnx/onnx', 0.5081114172935486, 'ml', 4), ('denys88/rl_games', 0.5077354311943054, 'ml-rl', 2), ('uber/petastorm', 0.5071843862533569, 'data', 3), ('graykode/nlp-tutorial', 0.5046815276145935, 'study', 2), ('tensorflow/lucid', 0.5045328140258789, 'ml-interpretability', 1), ('tensorlayer/tensorlayer', 0.5044419765472412, 'ml-rl', 2), ('nvidia/cuda-python', 0.5039113759994507, 'ml', 0), ('ml-explore/mlx', 0.5031680464744568, 'ml', 2), ('aistream-peelout/flow-forecast', 0.5023390650749207, 'time-series', 2), ('salesforce/deeptime', 0.5012999773025513, 'time-series', 1), ('huggingface/huggingface_hub', 0.5012728571891785, 'ml', 2), ('timdettmers/bitsandbytes', 0.5005117654800415, 'util', 0)]

26

8

null

1.92

16

10

65

0

5

2

5

16

22

90

1.4

57

1,142

util

https://github.com/eternnoir/pytelegrambotapi

[]

null

[]

null

eternnoir/pytelegrambotapi

pyTelegramBotAPI

7,429

1,975

225

Python

null

Python Telegram bot api.

eternnoir

2024-01-14

2015-06-26

448

16.561465

null

Python Telegram bot api.

['bot-api', 'python-api', 'telegram', 'telegram-bot', 'telegram-bot-api']

2024-01-12

[('mitmproxy/pdoc', 0.5450152158737183, 'util', 0), ('openai/gpt-discord-bot', 0.5340373516082764, 'llm', 0), ('pdoc3/pdoc', 0.5075708031654358, 'util', 0), ('hugapi/hug', 0.507483184337616, 'util', 1), ('freqtrade/freqtrade', 0.5027558207511902, 'crypto', 1), ('minimaxir/simpleaichat', 0.5022081732749939, 'llm', 0), ('vitalik/django-ninja', 0.5017293095588684, 'web', 0), ('togethercomputer/openchatkit', 0.5013675093650818, 'nlp', 0)]

228

2

null

4

66

63

104

0

7

8

7

67

200

90

3

57

409

web

https://github.com/encode/uvicorn

[]

null

[]

null

encode/uvicorn

uvicorn

7,420

685

91

Python

https://www.uvicorn.org/

An ASGI web server, for Python. 🦄

encode

2024-01-14

2017-05-31

347

21.330595

https://avatars.githubusercontent.com/u/19159390?v=4

An ASGI web server, for Python. 🦄

['asgi', 'asyncio', 'http', 'http-server']

2024-01-03

[('neoteroi/blacksheep', 0.8586666584014893, 'web', 4), ('encode/httpx', 0.8501601815223694, 'web', 2), ('pallets/quart', 0.8250173926353455, 'web', 3), ('aio-libs/aiohttp', 0.7939640879631042, 'web', 3), ('encode/starlette', 0.6668508052825928, 'web', 1), ('falconry/falcon', 0.6588360667228699, 'web', 2), ('klen/muffin', 0.6518058180809021, 'web', 2), ('cherrypy/cherrypy', 0.6493438482284546, 'web', 2), ('pylons/waitress', 0.6356403827667236, 'web', 1), ('huge-success/sanic', 0.633416473865509, 'web', 2), ('timofurrer/awesome-asyncio', 0.618058979511261, 'study', 1), ('psf/requests', 0.6152986884117126, 'web', 1), ('starlite-api/starlite', 0.6137245893478394, 'web', 2), ('alirn76/panther', 0.6067794561386108, 'web', 0), ('miguelgrinberg/python-socketio', 0.5958155989646912, 'util', 1), ('pallets/flask', 0.5909908413887024, 'web', 0), ('pallets/werkzeug', 0.5832026600837708, 'web', 1), ('jordaneremieff/mangum', 0.5822369456291199, 'web', 2), ('requests/toolbelt', 0.5721771717071533, 'util', 1), ('webpy/webpy', 0.5704232454299927, 'web', 0), ('reflex-dev/reflex', 0.5666500926017761, 'web', 0), ('masoniteframework/masonite', 0.5623204708099365, 'web', 0), ('pylons/pyramid', 0.5620464086532593, 'web', 0), ('benoitc/gunicorn', 0.5551705360412598, 'web', 2), ('python-trio/trio', 0.5339199304580688, 'perf', 0), ('bottlepy/bottle', 0.5337467193603516, 'web', 0), ('samuelcolvin/aioaws', 0.5331629514694214, 'data', 1), ('simple-salesforce/simple-salesforce', 0.5294420123100281, 'data', 0), ('emmett-framework/emmett', 0.514312207698822, 'web', 2), ('hugapi/hug', 0.5106011629104614, 'util', 2), ('sumerc/yappi', 0.5030171871185303, 'profiling', 2), ('websocket-client/websocket-client', 0.5029712319374084, 'web', 0), ('ets-labs/python-dependency-injector', 0.5008002519607544, 'util', 1)]

174

4

null

2.46

70

45

81

0

9

23

9

70

69

90

1

57

770

util

https://github.com/google/latexify_py

[]

null

[]

null

google/latexify_py

latexify_py

6,714

366

56

Python

null

A library to generate LaTeX expression from Python code.

google

2024-01-13

2020-07-25

183

36.602804

https://avatars.githubusercontent.com/u/1342004?v=4

A library to generate LaTeX expression from Python code.

[]

2023-12-08

[('connorferster/handcalcs', 0.7623890042304993, 'jupyter', 0), ('pytoolz/toolz', 0.6760282516479492, 'util', 0), ('julienpalard/pipe', 0.5925378799438477, 'util', 0), ('google/yapf', 0.5899499654769897, 'util', 0), ('pyston/pyston', 0.5858403444290161, 'util', 0), ('python/cpython', 0.5829751491546631, 'util', 0), ('pypy/pypy', 0.5807206630706787, 'util', 0), ('hhatto/autopep8', 0.5800272822380066, 'util', 0), ('pyparsing/pyparsing', 0.5657850503921509, 'util', 0), ('sympy/sympy', 0.5628668069839478, 'math', 0), ('pygments/pygments', 0.5412126183509827, 'util', 0), ('pyfpdf/fpdf2', 0.5399512052536011, 'util', 0), ('instagram/libcst', 0.5354775786399841, 'util', 0), ('grantjenks/blue', 0.5342947244644165, 'util', 0), ('python-markdown/markdown', 0.5334113240242004, 'util', 0), ('instagram/monkeytype', 0.5287166237831116, 'typing', 0), ('mnooner256/pyqrcode', 0.527988612651825, 'util', 0), ('python-rope/rope', 0.5269980430603027, 'util', 0), ('msaelices/py2mojo', 0.5220133662223816, 'util', 0), ('mynameisfiber/high_performance_python_2e', 0.518977165222168, 'study', 0), ('pyscf/pyscf', 0.5187242031097412, 'sim', 0), ('brandon-rhodes/python-patterns', 0.5185614824295044, 'util', 0), ('getpelican/pelican', 0.5140236020088196, 'web', 0), ('fchollet/deep-learning-with-python-notebooks', 0.5139066576957703, 'study', 0), ('sqlalchemy/mako', 0.5123310685157776, 'template', 0), ('psf/black', 0.5119499564170837, 'util', 0), ('microsoft/pycodegpt', 0.5082912445068359, 'llm', 0), ('numba/llvmlite', 0.5081674456596375, 'util', 0), ('eleutherai/pyfra', 0.5066225528717041, 'ml', 0), ('pmorissette/ffn', 0.5060634016990662, 'finance', 0), ('gbeced/pyalgotrade', 0.5051184296607971, 'finance', 0), ('has2k1/plotnine', 0.5012533068656921, 'viz', 0), ('nedbat/coveragepy', 0.5010238885879517, 'testing', 0)]

29

5

null

0.27

24

21

42

1

6

4

6

24

55

90

2.3

57

1,451

util

https://github.com/conda/conda

['package-manager', 'packaging']

null

[]

null

conda/conda

conda

5,923

1,467

197

Python

https://docs.conda.io/projects/conda/

A system-level, binary package and environment manager running on all major operating systems and platforms.

conda

2024-01-14

2012-10-15

589

10.053589

https://avatars.githubusercontent.com/u/6392739?v=4

A system-level, binary package and environment manager running on all major operating systems and platforms.

['conda', 'package-management']

['conda', 'package-management', 'package-manager', 'packaging']

2024-01-12

[('mamba-org/mamba', 0.752036988735199, 'util', 3), ('spack/spack', 0.7269142270088196, 'util', 1), ('pomponchik/instld', 0.6547331809997559, 'util', 1), ('indygreg/pyoxidizer', 0.5986080169677734, 'util', 2), ('conda/conda-build', 0.5913727283477783, 'util', 2), ('mamba-org/quetz', 0.5807616710662842, 'util', 1), ('mitsuhiko/rye', 0.5606615543365479, 'util', 2), ('mamba-org/boa', 0.5487179756164551, 'util', 1), ('pdm-project/pdm', 0.5474826097488403, 'util', 2), ('pypa/hatch', 0.5469714999198914, 'util', 2), ('tiiuae/sbomnix', 0.5382207632064819, 'util', 0), ('pypa/setuptools_scm', 0.532427966594696, 'util', 1), ('conda/conda-pack', 0.5275230407714844, 'util', 1), ('python-poetry/poetry', 0.527414858341217, 'util', 2), ('ofek/pyapp', 0.5070095658302307, 'util', 1)]

448

3

null

14.12

767

573

137

0

14

26

14

767

832

90

1.1

57

1,889

ml

https://github.com/kevinmusgrave/pytorch-metric-learning

['pytorch', 'embeddings']

null

[]

null

kevinmusgrave/pytorch-metric-learning

pytorch-metric-learning

5,618

646

65

Python

https://kevinmusgrave.github.io/pytorch-metric-learning/

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

kevinmusgrave

2024-01-14

2019-10-23

222

25.208974

null

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

['computer-vision', 'contrastive-learning', 'deep-learning', 'deep-metric-learning', 'embeddings', 'image-retrieval', 'machine-learning', 'metric-learning', 'pytorch', 'self-supervised-learning']

2023-12-16

[('oml-team/open-metric-learning', 0.7173192501068115, 'ml', 5), ('roboflow/supervision', 0.6149064302444458, 'ml', 4), ('scikit-learn-contrib/metric-learn', 0.5882241129875183, 'ml', 2), ('qdrant/quaterion', 0.584888219833374, 'ml', 5), ('lightly-ai/lightly', 0.581474244594574, 'ml', 7), ('tensorflow/tensorflow', 0.5597424507141113, 'ml-dl', 2), ('deci-ai/super-gradients', 0.5495540499687195, 'ml-dl', 3), ('huggingface/datasets', 0.5495465993881226, 'nlp', 4), ('pytorch/ignite', 0.5479029417037964, 'ml-dl', 3), ('gradio-app/gradio', 0.5473379492759705, 'viz', 2), ('mosaicml/composer', 0.5446270108222961, 'ml-dl', 3), ('keras-team/keras', 0.5415274500846863, 'ml-dl', 3), ('azavea/raster-vision', 0.5324239134788513, 'gis', 4), ('ddbourgin/numpy-ml', 0.5313518643379211, 'ml', 1), ('tensorflow/similarity', 0.5301912426948547, 'ml-dl', 4), ('onnx/onnx', 0.5226200222969055, 'ml', 3), ('datasystemslab/geotorch', 0.5219647884368896, 'gis', 1), ('huggingface/transformers', 0.5175970792770386, 'nlp', 3), ('kornia/kornia', 0.5158526301383972, 'ml-dl', 4), ('aiqc/aiqc', 0.5146724581718445, 'ml-ops', 0), ('awslabs/autogluon', 0.5119850635528564, 'ml', 4), ('nvlabs/gcvit', 0.5083329081535339, 'diffusion', 1), ('uber/petastorm', 0.5072482824325562, 'data', 3), ('albumentations-team/albumentations', 0.5062373876571655, 'ml-dl', 2), ('aleju/imgaug', 0.506173312664032, 'ml', 2), ('determined-ai/determined', 0.5060969591140747, 'ml-ops', 3), ('microsoft/nni', 0.5050148367881775, 'ml', 3), ('pytorch/torchrec', 0.5045345425605774, 'ml-dl', 2), ('ml-tooling/opyrator', 0.502253532409668, 'viz', 1), ('lutzroeder/netron', 0.5019212365150452, 'ml', 3), ('pyg-team/pytorch_geometric', 0.501497745513916, 'ml-dl', 2)]

40

6

null

2.56

24

18

51

1

13

12

13

24

54

90

2.2

57

354

ml-ops

https://github.com/feast-dev/feast

[]

null

[]

null

feast-dev/feast

feast

5,029

896

69

Python

https://feast.dev

Feature Store for Machine Learning

feast-dev

2024-01-14

2018-12-10

268

18.754928

https://avatars.githubusercontent.com/u/57027613?v=4

Feature Store for Machine Learning

['big-data', 'data-engineering', 'data-quality', 'data-science', 'feature-store', 'features', 'machine-learning', 'ml', 'mlops']

2024-01-13

[('featureform/embeddinghub', 0.7385993599891663, 'nlp', 6), ('polyaxon/polyaxon', 0.6851301193237305, 'ml-ops', 4), ('netflix/metaflow', 0.6503940224647522, 'ml-ops', 4), ('firmai/industry-machine-learning', 0.6406149864196777, 'study', 2), ('kubeflow/pipelines', 0.6390533447265625, 'ml-ops', 3), ('onnx/onnx', 0.6326718330383301, 'ml', 2), ('mlflow/mlflow', 0.6303765773773193, 'ml-ops', 2), ('bentoml/bentoml', 0.6025741696357727, 'ml-ops', 2), ('huggingface/datasets', 0.5980408191680908, 'nlp', 1), ('googlecloudplatform/vertex-ai-samples', 0.595111072063446, 'ml', 3), ('hpcaitech/colossalai', 0.585966944694519, 'llm', 0), ('xplainable/xplainable', 0.5823587775230408, 'ml-interpretability', 2), ('activeloopai/deeplake', 0.5807369947433472, 'ml-ops', 4), ('polyaxon/datatile', 0.570514976978302, 'pandas', 3), ('tensorflow/tensorflow', 0.5688017010688782, 'ml-dl', 2), ('microsoft/nni', 0.5683546662330627, 'ml', 3), ('mage-ai/mage-ai', 0.5513089299201965, 'ml-ops', 3), ('alirezadir/machine-learning-interview-enlightener', 0.5510007739067078, 'study', 1), ('whylabs/whylogs', 0.5498430132865906, 'util', 4), ('fatiando/verde', 0.5436317324638367, 'gis', 1), ('sktime/sktime', 0.5417338609695435, 'time-series', 2), ('winedarksea/autots', 0.5365046262741089, 'time-series', 1), ('mosaicml/composer', 0.535942554473877, 'ml-dl', 1), ('online-ml/river', 0.5350134372711182, 'ml', 2), ('ploomber/ploomber', 0.5336986780166626, 'ml-ops', 4), ('superduperdb/superduperdb', 0.530910313129425, 'data', 2), ('bodywork-ml/bodywork-core', 0.5267590284347534, 'ml-ops', 3), ('lancedb/lancedb', 0.5253369808197021, 'data', 0), ('great-expectations/great_expectations', 0.5238198041915894, 'ml-ops', 4), ('milvus-io/bootcamp', 0.5231591463088989, 'data', 0), ('keras-team/keras', 0.5223841071128845, 'ml-dl', 2), ('scikit-learn/scikit-learn', 0.5212818384170532, 'ml', 2), ('avaiga/taipy', 0.5180974006652832, 'data', 2), ('google/mediapipe', 0.5142419338226318, 'ml', 1), ('qdrant/qdrant', 0.5136101245880127, 'data', 2), ('ml-tooling/opyrator', 0.5118728876113892, 'viz', 1), ('iterative/dvc', 0.5111587047576904, 'ml-ops', 2), ('giskard-ai/giskard', 0.507591962814331, 'data', 2), ('gradio-app/gradio', 0.5052893757820129, 'viz', 2), ('google-research/google-research', 0.5038433074951172, 'ml', 1), ('krzjoa/awesome-python-data-science', 0.5033879280090332, 'study', 2), ('explosion/thinc', 0.5021685361862183, 'ml-dl', 1), ('nccr-itmo/fedot', 0.5015140175819397, 'ml-ops', 1), ('mindsdb/mindsdb', 0.5014446973800659, 'data', 2)]

222

4

null

3.38

118

52

62

0

13

27

13

117

126

90

1.1

57

227

ml

https://github.com/online-ml/river

[]

null

[]

1

null

online-ml/river

river

4,605

551

85

Python

https://riverml.xyz

🌊 Online machine learning in Python

online-ml

2024-01-13

2019-01-24

261

17.595524

https://avatars.githubusercontent.com/u/47002673?v=4

🌊 Online machine learning in Python

['concept-drift', 'data-science', 'incremental-learning', 'machine-learning', 'online-learning', 'online-machine-learning', 'online-statistics', 'real-time-processing', 'stream-processing', 'streaming', 'streaming-data']

2024-01-01

[('scikit-learn/scikit-learn', 0.6860164403915405, 'ml', 2), ('jeshraghian/snntorch', 0.615203320980072, 'ml-dl', 1), ('gradio-app/gradio', 0.6122671961784363, 'viz', 2), ('ddbourgin/numpy-ml', 0.6021139025688171, 'ml', 1), ('xplainable/xplainable', 0.584074079990387, 'ml-interpretability', 2), ('pycaret/pycaret', 0.5788997411727905, 'ml', 2), ('ml-tooling/opyrator', 0.574630618095398, 'viz', 1), ('rasbt/mlxtend', 0.5713738799095154, 'ml', 2), ('polyaxon/datatile', 0.5639887452125549, 'pandas', 1), ('awslabs/gluonts', 0.5579661130905151, 'time-series', 2), ('tensorly/tensorly', 0.5535548329353333, 'ml-dl', 1), ('jovianml/opendatasets', 0.5532159209251404, 'data', 2), ('merantix-momentum/squirrel-core', 0.5505257248878479, 'ml', 2), ('google/mediapipe', 0.541152834892273, 'ml', 2), ('firmai/atspy', 0.5391773581504822, 'time-series', 0), ('mlflow/mlflow', 0.5388703346252441, 'ml-ops', 1), ('pathwaycom/pathway', 0.5360531210899353, 'data', 1), ('tensorflow/tensorflow', 0.5353706479072571, 'ml-dl', 1), ('feast-dev/feast', 0.5350134372711182, 'ml-ops', 2), ('clips/pattern', 0.5316668152809143, 'nlp', 1), ('featurelabs/featuretools', 0.5314729809761047, 'ml', 2), ('fatiando/verde', 0.531051754951477, 'gis', 1), ('sktime/sktime', 0.5300047993659973, 'time-series', 2), ('statsmodels/statsmodels', 0.5298870205879211, 'ml', 1), ('firmai/industry-machine-learning', 0.5276996493339539, 'study', 2), ('thealgorithms/python', 0.5223714709281921, 'study', 0), ('automl/auto-sklearn', 0.5197332501411438, 'ml', 0), ('scikit-mobility/scikit-mobility', 0.5196621417999268, 'gis', 1), ('nccr-itmo/fedot', 0.5161853432655334, 'ml-ops', 1), ('dylanhogg/awesome-python', 0.5161080360412598, 'study', 2), ('reloadware/reloadium', 0.5157492160797119, 'profiling', 0), ('sentinel-hub/eo-learn', 0.5141457915306091, 'gis', 1), ('probml/pyprobml', 0.5124793648719788, 'ml', 1), ('scikit-learn-contrib/imbalanced-learn', 0.5116428732872009, 'ml', 2), ('quantconnect/lean', 0.511631429195404, 'finance', 0), ('ai4finance-foundation/finrl', 0.5111426711082458, 'finance', 0), ('epistasislab/tpot', 0.5093849897384644, 'ml', 2), ('crflynn/stochastic', 0.507440447807312, 'sim', 0), ('google/trax', 0.5071595311164856, 'ml-dl', 1), ('eventual-inc/daft', 0.506720244884491, 'pandas', 2), ('googlecloudplatform/vertex-ai-samples', 0.505128800868988, 'ml', 1), ('google/temporian', 0.5042147040367126, 'time-series', 0), ('ranaroussi/quantstats', 0.5004301071166992, 'finance', 0)]

108

6

null

5.67

137

31

61

0

7

137

161

90

1.2

57

887

time-series

https://github.com/awslabs/gluonts

[]

null

[]

null

awslabs/gluonts

gluonts

4,008

758

74

Python

https://ts.gluon.ai

Probabilistic time series modeling in Python

awslabs

2024-01-12

2019-05-15

245

16.30215

https://avatars.githubusercontent.com/u/3299148?v=4

Probabilistic time series modeling in Python

['artificial-intelligence', 'aws', 'data-science', 'deep-learning', 'forecasting', 'machine-learning', 'mxnet', 'neural-networks', 'pytorch', 'sagemaker', 'time-series', 'time-series-forecasting', 'time-series-prediction', 'timeseries', 'torch']

2024-01-10

[('firmai/atspy', 0.695907711982727, 'time-series', 2), ('alkaline-ml/pmdarima', 0.6824057102203369, 'time-series', 3), ('unit8co/darts', 0.6495864987373352, 'time-series', 5), ('uber/orbit', 0.6446792483329773, 'time-series', 4), ('rjt1990/pyflux', 0.623365581035614, 'time-series', 1), ('scikit-learn/scikit-learn', 0.6101686358451843, 'ml', 2), ('crflynn/stochastic', 0.5971387624740601, 'sim', 0), ('pymc-devs/pymc3', 0.593370795249939, 'ml', 0), ('probml/pyprobml', 0.5823290348052979, 'ml', 2), ('aistream-peelout/flow-forecast', 0.5800959467887878, 'time-series', 5), ('salesforce/deeptime', 0.5721127390861511, 'time-series', 4), ('pycaret/pycaret', 0.5713929533958435, 'ml', 3), ('statsmodels/statsmodels', 0.5710023641586304, 'ml', 2), ('ddbourgin/numpy-ml', 0.5705474615097046, 'ml', 2), ('google/temporian', 0.5661502480506897, 'time-series', 1), ('ourownstory/neural_prophet', 0.5649511814117432, 'ml', 7), ('winedarksea/autots', 0.5618434548377991, 'time-series', 4), ('sktime/sktime', 0.5607674717903137, 'time-series', 4), ('online-ml/river', 0.5579661130905151, 'ml', 2), ('tdameritrade/stumpy', 0.5509535074234009, 'time-series', 1), ('pyro-ppl/pyro', 0.5475439429283142, 'ml-dl', 3), ('salesforce/merlion', 0.5388320684432983, 'time-series', 3), ('microprediction/microprediction', 0.5331199765205383, 'time-series', 2), ('bashtage/arch', 0.5267676115036011, 'time-series', 2), ('jeshraghian/snntorch', 0.5149070620536804, 'ml-dl', 3), ('nixtla/statsforecast', 0.5115534067153931, 'time-series', 4), ('gradio-app/gradio', 0.5049344301223755, 'viz', 3), ('opengeos/earthformer', 0.502416729927063, 'gis', 2)]

110

5

null

5.29

96

63

57

0

34

23

34

96

130

90

1.4

57

1,608

llm

https://github.com/openbmb/toolbench

['instruction-tuning', 'evaluation']

null

[]

null

openbmb/toolbench

ToolBench

3,959

336

49

Python

https://openbmb.github.io/ToolBench/

An open platform for training, serving, and evaluating large language model for tool learning.

openbmb

2024-01-14

2023-05-28

35

112.198381

https://avatars.githubusercontent.com/u/89920203?v=4

An open platform for training, serving, and evaluating large language model for tool learning.

[]

['evaluation', 'instruction-tuning']

2023-11-22

[('lm-sys/fastchat', 0.7016268968582153, 'llm', 1), ('ai21labs/lm-evaluation', 0.6778345704078674, 'llm', 0), ('conceptofmind/toolformer', 0.6644108891487122, 'llm', 0), ('ctlllll/llm-toolmaker', 0.6306527853012085, 'llm', 0), ('night-chen/toolqa', 0.6098852753639221, 'llm', 0), ('lucidrains/toolformer-pytorch', 0.5833466649055481, 'llm', 0), ('bigscience-workshop/biomedical', 0.5767196416854858, 'data', 0), ('argilla-io/argilla', 0.5743700265884399, 'nlp', 0), ('lianjiatech/belle', 0.5728527903556824, 'llm', 0), ('openlmlab/leval', 0.5642274022102356, 'llm', 1), ('llmware-ai/llmware', 0.5629839301109314, 'llm', 0), ('optimalscale/lmflow', 0.5591222643852234, 'llm', 0), ('juncongmoo/pyllama', 0.5528221130371094, 'llm', 0), ('eleutherai/lm-evaluation-harness', 0.5517364740371704, 'llm', 1), ('young-geng/easylm', 0.5505062341690063, 'llm', 0), ('hannibal046/awesome-llm', 0.5423779487609863, 'study', 0), ('yizhongw/self-instruct', 0.542241096496582, 'llm', 1), ('hegelai/prompttools', 0.5396706461906433, 'llm', 0), ('hiyouga/llama-factory', 0.5351808667182922, 'llm', 1), ('hiyouga/llama-efficient-tuning', 0.5351806879043579, 'llm', 1), ('databrickslabs/dolly', 0.5324987173080444, 'llm', 0), ('freedomintelligence/llmzoo', 0.5291275978088379, 'llm', 0), ('openlmlab/moss', 0.5276908278465271, 'llm', 0), ('tatsu-lab/stanford_alpaca', 0.5260429382324219, 'llm', 0), ('huggingface/evaluate', 0.5237149000167847, 'ml', 1), ('agenta-ai/agenta', 0.5236167907714844, 'llm', 0), ('jonasgeiping/cramming', 0.521796703338623, 'nlp', 0), ('luohongyin/sail', 0.5190768241882324, 'llm', 0), ('airi-institute/probing_framework', 0.5175856351852417, 'nlp', 0), ('alpha-vllm/llama2-accessory', 0.5172504186630249, 'llm', 0), ('cg123/mergekit', 0.5107592344284058, 'llm', 0), ('keirp/automatic_prompt_engineer', 0.5084372758865356, 'llm', 0), ('salesforce/codet5', 0.5070496201515198, 'nlp', 0), ('confident-ai/deepeval', 0.5041009783744812, 'testing', 1), ('next-gpt/next-gpt', 0.5017238259315491, 'llm', 1), ('guidance-ai/guidance', 0.5015900135040283, 'llm', 0), ('tigerlab-ai/tiger', 0.5014435052871704, 'llm', 0), ('huggingface/text-generation-inference', 0.5014093518257141, 'llm', 0), ('microsoft/unilm', 0.5009614825248718, 'nlp', 0)]

16

3

null

2.83

63

24

8

2

0

63

90

1

57

1,770

typing

https://github.com/python/typeshed

['code-quality']

null

[]

null

python/typeshed

typeshed

3,908

1,680

78

Python

null

Collection of library stubs for Python, with static types

python

2024-01-13

2015-03-05

464

8.409468

https://avatars.githubusercontent.com/u/1525981?v=4

Collection of library stubs for Python, with static types

['stub', 'types', 'typing']

['code-quality', 'stub', 'types', 'typing']

2024-01-12

[('instagram/monkeytype', 0.723702609539032, 'typing', 1), ('google/pytype', 0.7091848254203796, 'typing', 3), ('python/mypy', 0.6911789178848267, 'typing', 3), ('microsoft/pyright', 0.6651108264923096, 'typing', 1), ('pytoolz/toolz', 0.5580030083656311, 'util', 0), ('facebook/pyre-check', 0.5521007180213928, 'typing', 1), ('agronholm/typeguard', 0.5519527792930603, 'typing', 1), ('astral-sh/ruff', 0.5103850364685059, 'util', 1), ('landscapeio/prospector', 0.509270191192627, 'util', 0)]

1,367

5

null

22.35

463

365

108

0

463

1,257

90

2.7

57

269

web

https://github.com/strawberry-graphql/strawberry

[]

null

[]

null

strawberry-graphql/strawberry

strawberry

3,613

484

44

Python

https://strawberry.rocks

A GraphQL library for Python that leverages type annotations 🍓

strawberry-graphql

2024-01-13

2018-12-21

266

13.553591

https://avatars.githubusercontent.com/u/48071860?v=4

A GraphQL library for Python that leverages type annotations 🍓

['asgi', 'asyncio', 'django', 'graphql', 'graphql-library', 'graphql-schema', 'graphql-server', 'mypy', 'starlette', 'strawberry']

2024-01-07

[('instagram/monkeytype', 0.6149357557296753, 'typing', 0), ('patrick-kidger/torchtyping', 0.5875641703605652, 'typing', 0), ('facebook/pyre-check', 0.5584018230438232, 'typing', 0), ('accenture/ampligraph', 0.5520169734954834, 'data', 0), ('tiangolo/sqlmodel', 0.5469264984130859, 'data', 0), ('jsonpickle/jsonpickle', 0.5452963709831238, 'data', 0), ('sqlalchemy/sqlalchemy', 0.5367457866668701, 'data', 0), ('pytoolz/toolz', 0.5352164506912231, 'util', 0), ('plotly/plotly.py', 0.5247325897216797, 'viz', 0), ('tobymao/sqlglot', 0.5215062499046326, 'data', 0), ('marshmallow-code/marshmallow', 0.5134101510047913, 'util', 0), ('mcfunley/pugsql', 0.5126366019248962, 'data', 0), ('typesense/typesense-python', 0.5120099782943726, 'data', 0), ('ibis-project/ibis', 0.5083762407302856, 'data', 0), ('aws/graph-notebook', 0.5056154131889343, 'jupyter', 0), ('s3rius/fastapi-template', 0.5046817064285278, 'web', 2), ('pydantic/pydantic', 0.5045525431632996, 'util', 0), ('nicolas-hbt/pygraft', 0.5039038062095642, 'ml', 0)]

237

5

null

9.63

643

186

62

0

164

131

164

643

664

90

1

57

1,092

llm

https://github.com/eleutherai/lm-evaluation-harness

['benchmark', 'evaluation', 'language-model']

null

[]

null

eleutherai/lm-evaluation-harness

lm-evaluation-harness

3,589

921

34

Python

https://www.eleuther.ai

A framework for few-shot evaluation of language models.

eleutherai

2024-01-14

2020-08-28

178

20.0984

https://avatars.githubusercontent.com/u/68924597?v=4

A framework for few-shot evaluation of language models.

['evaluation-framework', 'language-model', 'transformer']

['benchmark', 'evaluation', 'evaluation-framework', 'language-model', 'transformer']

2024-01-12

[('ai21labs/lm-evaluation', 0.7471644282341003, 'llm', 2), ('huggingface/setfit', 0.6814461350440979, 'nlp', 0), ('freedomintelligence/llmzoo', 0.6675116419792175, 'llm', 1), ('openlmlab/leval', 0.6121481657028198, 'llm', 2), ('juncongmoo/pyllama', 0.6021994948387146, 'llm', 0), ('lm-sys/fastchat', 0.6016319394111633, 'llm', 2), ('reasoning-machines/pal', 0.5877846479415894, 'llm', 1), ('cg123/mergekit', 0.5827073454856873, 'llm', 0), ('hannibal046/awesome-llm', 0.5770836472511292, 'study', 1), ('jonasgeiping/cramming', 0.5666804909706116, 'nlp', 1), ('nvlabs/prismer', 0.5629435777664185, 'diffusion', 1), ('anthropics/evals', 0.5547993183135986, 'llm', 0), ('ctlllll/llm-toolmaker', 0.5522134304046631, 'llm', 1), ('openbmb/toolbench', 0.5517364740371704, 'llm', 1), ('bigscience-workshop/biomedical', 0.5494688153266907, 'data', 0), ('lianjiatech/belle', 0.5487149953842163, 'llm', 0), ('srush/minichain', 0.542423665523529, 'llm', 0), ('huggingface/evaluate', 0.5417475700378418, 'ml', 1), ('yueyu1030/attrprompt', 0.5361191034317017, 'llm', 0), ('fasteval/fasteval', 0.5358782410621643, 'llm', 2), ('mit-han-lab/streaming-llm', 0.5352895259857178, 'llm', 0), ('ofa-sys/ofa', 0.5323944091796875, 'llm', 0), ('salesforce/blip', 0.5254507064819336, 'diffusion', 0), ('microsoft/lora', 0.5240524411201477, 'llm', 1), ('ai21labs/in-context-ralm', 0.5203155875205994, 'llm', 1), ('alibaba/easynlp', 0.520174503326416, 'nlp', 0), ('explosion/spacy-models', 0.5173574686050415, 'nlp', 0), ('yizhongw/self-instruct', 0.513164758682251, 'llm', 1), ('young-geng/easylm', 0.5126963257789612, 'llm', 2), ('jina-ai/finetuner', 0.5112559199333191, 'ml', 0), ('conceptofmind/toolformer', 0.5054224729537964, 'llm', 1), ('next-gpt/next-gpt', 0.5040009617805481, 'llm', 0)]

103

2

null

29.67

484

372

41

0

1

484

1,016

90

2.1

57

486

util

https://github.com/pydata/xarray

[]

null

[]

null

pydata/xarray

xarray

3,318

996

109

Python

https://xarray.dev

N-D labeled arrays and datasets in Python

pydata

2024-01-13

2013-09-30

539

6.154213

https://avatars.githubusercontent.com/u/1284191?v=4

N-D labeled arrays and datasets in Python

['dask', 'netcdf', 'numpy', 'pandas', 'xarray']

2024-01-08

[('holoviz/hvplot', 0.5328260064125061, 'pandas', 0), ('zarr-developers/zarr-python', 0.5044090151786804, 'data', 0)]

465

6

null

9.1

425

283

125

0

15

9

15

425

1,167

90

2.7

57

1,298

ml-ops

https://github.com/determined-ai/determined

[]

null

[]

null

determined-ai/determined

determined

2,696

338

75

Go

https://determined.ai

Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.

determined-ai

2024-01-13

2020-04-07

199

13.547739

https://avatars.githubusercontent.com/u/26636771?v=4

Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.

['data-science', 'deep-learning', 'distributed-training', 'hyperparameter-optimization', 'hyperparameter-search', 'hyperparameter-tuning', 'keras', 'kubernetes', 'machine-learning', 'ml-infrastructure', 'ml-platform', 'mlops', 'pytorch', 'tensorflow']

2024-01-12

[('tensorflow/tensorflow', 0.7361361384391785, 'ml-dl', 3), ('horovod/horovod', 0.6985735297203064, 'ml-ops', 5), ('microsoft/deepspeed', 0.6881573796272278, 'ml-dl', 3), ('mlflow/mlflow', 0.6798075437545776, 'ml-ops', 1), ('wandb/client', 0.6777682900428772, 'ml', 11), ('polyaxon/polyaxon', 0.6687636971473694, 'ml-ops', 9), ('microsoft/nni', 0.6512665748596191, 'ml', 8), ('microsoft/onnxruntime', 0.643320620059967, 'ml', 4), ('rasbt/machine-learning-book', 0.6383908987045288, 'study', 3), ('ray-project/ray', 0.6333746314048767, 'ml-ops', 7), ('intel/intel-extension-for-pytorch', 0.6318769454956055, 'perf', 3), ('google/vizier', 0.6237358450889587, 'ml', 4), ('optuna/optuna', 0.6228476166725159, 'ml', 2), ('ashleve/lightning-hydra-template', 0.6221935153007507, 'util', 3), ('aimhubio/aim', 0.614514172077179, 'ml-ops', 5), ('pytorch/ignite', 0.6104621291160583, 'ml-dl', 3), ('uber/petastorm', 0.6062763929367065, 'data', 4), ('paddlepaddle/paddle', 0.6040452122688293, 'ml-dl', 3), ('automl/auto-sklearn', 0.6021798253059387, 'ml', 3), ('huggingface/datasets', 0.599459171295166, 'nlp', 4), ('merantix-momentum/squirrel-core', 0.5961888432502747, 'ml', 5), ('aws/sagemaker-python-sdk', 0.5937497019767761, 'ml', 3), ('kubeflow-kale/kale', 0.5921743512153625, 'ml-ops', 1), ('onnx/onnx', 0.5901457667350769, 'ml', 5), ('tensorflow/tensor2tensor', 0.5887267589569092, 'ml', 2), ('kubeflow/katib', 0.5883219242095947, 'ml', 0), ('tlkh/tf-metal-experiments', 0.5877756476402283, 'perf', 2), ('googlecloudplatform/vertex-ai-samples', 0.5860880613327026, 'ml', 2), ('adap/flower', 0.5839700698852539, 'ml-ops', 4), ('ageron/handson-ml2', 0.5803431868553162, 'ml', 0), ('firmai/industry-machine-learning', 0.574253261089325, 'study', 2), ('alpa-projects/alpa', 0.571927547454834, 'ml-dl', 3), ('microsoft/flaml', 0.5710462927818298, 'ml', 4), ('nvidia/deeplearningexamples', 0.5695421099662781, 'ml-dl', 3), ('eleutherai/oslo', 0.56780606508255, 'ml', 0), ('epistasislab/tpot', 0.5670955777168274, 'ml', 3), ('tensorlayer/tensorlayer', 0.5628274083137512, 'ml-rl', 2), ('deepchecks/deepchecks', 0.5619574189186096, 'data', 5), ('ddbourgin/numpy-ml', 0.5607567429542542, 'ml', 1), ('nevronai/metisfl', 0.5598009824752808, 'ml', 2), ('uber/fiber', 0.5588817596435547, 'data', 1), ('keras-rl/keras-rl', 0.5585846900939941, 'ml-rl', 3), ('nccr-itmo/fedot', 0.5581679940223694, 'ml-ops', 2), ('nvidia/apex', 0.5580594539642334, 'ml-dl', 0), ('huggingface/transformers', 0.5561276078224182, 'nlp', 4), ('keras-team/keras', 0.5539653301239014, 'ml-dl', 5), ('pytorchlightning/pytorch-lightning', 0.55375736951828, 'ml-dl', 4), ('gradio-app/gradio', 0.5533111095428467, 'viz', 3), ('mosaicml/composer', 0.5523366332054138, 'ml-dl', 3), ('lutzroeder/netron', 0.5507928729057312, 'ml', 5), ('aiqc/aiqc', 0.5507001280784607, 'ml-ops', 0), ('bigscience-workshop/petals', 0.5506836771965027, 'data', 3), ('apache/incubator-mxnet', 0.5505608320236206, 'ml-dl', 0), ('neuralmagic/deepsparse', 0.5497815608978271, 'nlp', 0), ('google/trax', 0.5475213527679443, 'ml-dl', 2), ('google/tf-quant-finance', 0.5471197366714478, 'finance', 1), ('unity-technologies/ml-agents', 0.5427035689353943, 'ml-rl', 2), ('skorch-dev/skorch', 0.5415751338005066, 'ml-dl', 2), ('titanml/takeoff', 0.5414642691612244, 'llm', 0), ('hyperopt/hyperopt', 0.5405532121658325, 'ml', 0), ('denys88/rl_games', 0.5401771664619446, 'ml-rl', 2), ('kubeflow/pipelines', 0.5401206016540527, 'ml-ops', 4), ('salesforce/warp-drive', 0.5399549603462219, 'ml-rl', 2), ('bentoml/bentoml', 0.5386102795600891, 'ml-ops', 5), ('microsoft/jarvis', 0.5367454290390015, 'llm', 2), ('pytorch/rl', 0.5359745025634766, 'ml-rl', 2), ('huggingface/evaluate', 0.5355773568153381, 'ml', 1), ('koaning/human-learn', 0.5347359776496887, 'data', 1), ('karpathy/micrograd', 0.5347241163253784, 'study', 0), ('intel/scikit-learn-intelex', 0.534125566482544, 'perf', 1), ('tigerlab-ai/tiger', 0.5315389633178711, 'llm', 0), ('deepmind/dm_control', 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'ml', 0), ('zenml-io/zenml', 0.5032854676246643, 'ml-ops', 6), ('iryna-kondr/scikit-llm', 0.5017955303192139, 'llm', 2), ('d2l-ai/d2l-en', 0.5009527802467346, 'study', 7)]

108

2

null

44.23

661

550

46

0

27

131

27

660

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57

1,570

llm

https://github.com/tairov/llama2.mojo

['mojo']

null

[]

null

tairov/llama2.mojo

llama2.mojo

1,773

111

23

Python

https://www.modular.com/blog/community-spotlight-how-i-built-llama2-by-aydyn-tairov

Inference Llama 2 in one file of pure 🔥

tairov

2024-01-12

2023-09-10

20

87.401408

null

Inference Llama 2 in one file of pure 🔥

['inference', 'llama', 'llama2', 'modular', 'mojo', 'parallelize', 'performance', 'simd', 'tensor', 'transformer-architecture', 'vectorization']

2023-12-06

[('karpathy/llama2.c', 0.8035979270935059, 'llm', 1), ('facebookresearch/llama', 0.7085148692131042, 'llm', 1), ('facebookresearch/llama-recipes', 0.6153814792633057, 'llm', 1), ('microsoft/llama-2-onnx', 0.6118836998939514, 'llm', 1), ('facebookresearch/codellama', 0.599827229976654, 'llm', 1), ('vllm-project/vllm', 0.5809930562973022, 'llm', 2), ('mshumer/gpt-llm-trainer', 0.5809900760650635, 'llm', 0), ('bentoml/openllm', 0.5740443468093872, 'ml-ops', 2), ('predibase/lorax', 0.568372368812561, 'llm', 1), ('bigscience-workshop/petals', 0.537801206111908, 'data', 2), ('jzhang38/tinyllama', 0.5322071313858032, 'llm', 1), ('bobazooba/xllm', 0.5215964913368225, 'llm', 2), ('titanml/takeoff', 0.5167184472084045, 'llm', 2), ('openlm-research/open_llama', 0.5117022395133972, 'llm', 1), ('run-llama/llama-lab', 0.5075839757919312, 'llm', 1), ('tloen/alpaca-lora', 0.5015569925308228, 'llm', 1), ('lightning-ai/lit-llama', 0.501312792301178, 'llm', 1)]

12

4

null

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430

study

https://github.com/jakevdp/pythondatasciencehandbook

[]

null

[]

null

jakevdp/pythondatasciencehandbook

PythonDataScienceHandbook

40,567

17,512

1,772

Jupyter Notebook

http://jakevdp.github.io/PythonDataScienceHandbook

Python Data Science Handbook: full text in Jupyter Notebooks

jakevdp

2024-01-14

2016-08-10

389

104.056064

null

Python Data Science Handbook: full text in Jupyter Notebooks

['jupyter-notebook', 'matplotlib', 'numpy', 'pandas', 'scikit-learn']

2023-05-05

[('wesm/pydata-book', 0.7202770709991455, 'study', 0), ('jupyter/nbformat', 0.6972000598907471, 'jupyter', 0), ('ageron/handson-ml2', 0.6813152432441711, 'ml', 0), ('tkrabel/bamboolib', 0.6585032939910889, 'pandas', 2), ('fchollet/deep-learning-with-python-notebooks', 0.6521231532096863, 'study', 0), ('mwaskom/seaborn', 0.6520794630050659, 'viz', 2), ('quantopian/qgrid', 0.6440531611442566, 'jupyter', 0), ('man-group/dtale', 0.6342079639434814, 'viz', 2), ('holoviz/panel', 0.6207575798034668, 'viz', 1), ('cohere-ai/notebooks', 0.6190292835235596, 'llm', 0), ('vizzuhq/ipyvizzu', 0.6107296943664551, 'jupyter', 1), ('lux-org/lux', 0.5983377695083618, 'viz', 1), ('jupyter/nbconvert', 0.5953406095504761, 'jupyter', 0), ('ipython/ipyparallel', 0.5817736983299255, 'perf', 0), ('ipython/ipykernel', 0.5796281099319458, 'util', 1), ('jupyterlab/jupyterlab', 0.5746160745620728, 'jupyter', 0), ('numpy/numpy', 0.5711981654167175, 'math', 1), ('matplotlib/matplotlib', 0.5707853436470032, 'viz', 1), ('jupyter-widgets/ipywidgets', 0.5679361820220947, 'jupyter', 0), ('maartenbreddels/ipyvolume', 0.5677738189697266, 'jupyter', 1), ('jupyter/notebook', 0.5674871206283569, 'jupyter', 1), ('eleutherai/pyfra', 0.5671376585960388, 'ml', 0), ('holoviz/hvplot', 0.5669666528701782, 'pandas', 0), ('opengeos/leafmap', 0.5667238235473633, 'gis', 1), ('altair-viz/altair', 0.5655259490013123, 'viz', 0), ('pyqtgraph/pyqtgraph', 0.5645138621330261, 'viz', 1), ('kanaries/pygwalker', 0.5599751472473145, 'pandas', 2), ('aws/graph-notebook', 0.559874951839447, 'jupyter', 1), ('residentmario/geoplot', 0.5592259168624878, 'gis', 1), ('holoviz/holoviz', 0.5567380785942078, 'viz', 0), ('koaning/drawdata', 0.5549478530883789, 'jupyter', 0), ('jupyterlab/jupyterlab-desktop', 0.5509034395217896, 'jupyter', 1), ('mynameisfiber/high_performance_python_2e', 0.5477574467658997, 'study', 0), ('mito-ds/monorepo', 0.5431113243103027, 'jupyter', 1), ('vaexio/vaex', 0.5422857999801636, 'perf', 0), ('plotly/plotly.py', 0.5420818328857422, 'viz', 1), ('blaze/blaze', 0.5417280793190002, 'pandas', 0), ('mwouts/jupytext', 0.5404434204101562, 'jupyter', 1), ('enthought/mayavi', 0.5390788912773132, 'viz', 0), ('python/cpython', 0.5353503823280334, 'util', 0), ('goldmansachs/gs-quant', 0.533323347568512, 'finance', 0), ('realpython/python-guide', 0.5322774648666382, 'study', 0), ('geopandas/geopandas', 0.531819760799408, 'gis', 1), ('contextlab/hypertools', 0.5308850407600403, 'ml', 0), ('scipy/scipy', 0.5299432873725891, 'math', 0), ('scitools/cartopy', 0.5279793739318848, 'gis', 1), ('bloomberg/ipydatagrid', 0.5277616381645203, 'jupyter', 0), ('jupyter/nbdime', 0.5264706611633301, 'jupyter', 1), ('bokeh/bokeh', 0.5242840051651001, 'viz', 0), ('pandas-dev/pandas', 0.5242447853088379, 'pandas', 1), ('marcomusy/vedo', 0.5232061743736267, 'viz', 1), ('has2k1/plotnine', 0.5220550894737244, 'viz', 0), ('roban/cosmolopy', 0.5194147229194641, 'sim', 0), ('plotly/dash', 0.5179597735404968, 'viz', 0), ('voila-dashboards/voila', 0.5165765881538391, 'jupyter', 1), ('krzjoa/awesome-python-data-science', 0.5150753259658813, 'study', 1), ('jupyter/nbgrader', 0.5142012238502502, 'jupyter', 1), ('amaargiru/pyroad', 0.5113055109977722, 'study', 0), ('cmudig/autoprofiler', 0.5069370865821838, 'jupyter', 1), ('mementum/bta-lib', 0.5062484741210938, 'finance', 0), ('rasbt/mlxtend', 0.5061179399490356, 'ml', 0), ('cuemacro/chartpy', 0.5052139759063721, 'viz', 1), ('scitools/iris', 0.5051771402359009, 'gis', 0), ('jazzband/tablib', 0.5034573078155518, 'data', 0), ('scikit-learn-contrib/sklearn-pandas', 0.5033451914787292, 'pandas', 0), ('jupyter-widgets/ipyleaflet', 0.5016043186187744, 'gis', 0)]

17

7

null

0.02

8

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90

8

0

8

3

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128

ml

https://github.com/microsoft/nni

[]

null

[]

null

microsoft/nni

nni

13,495

1,829

284

Python

https://nni.readthedocs.io

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

microsoft

2024-01-13

2018-06-01

295

45.657322

https://avatars.githubusercontent.com/u/6154722?v=4

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

['automated-machine-learning', 'automl', 'bayesian-optimization', 'data-science', 'deep-learning', 'deep-neural-network', 'distributed', 'feature-engineering', 'hyperparameter-optimization', 'hyperparameter-tuning', 'machine-learning', 'machine-learning-algorithms', 'mlops', 'model-compression', 'nas', 'neural-architecture-search', 'neural-network', 'pytorch', 'tensorflow']

2023-10-26

[('keras-team/autokeras', 0.8086925148963928, 'ml-dl', 6), ('microsoft/flaml', 0.7865293025970459, 'ml', 6), ('automl/auto-sklearn', 0.7624291777610779, 'ml', 5), ('awslabs/autogluon', 0.7000966668128967, 'ml', 7), ('nccr-itmo/fedot', 0.6999444365501404, 'ml-ops', 4), ('mlflow/mlflow', 0.6970524191856384, 'ml-ops', 1), ('mljar/mljar-supervised', 0.6952623724937439, 'ml', 7), ('polyaxon/polyaxon', 0.6834843754768372, 'ml-ops', 7), ('winedarksea/autots', 0.6789240837097168, 'time-series', 4), ('featurelabs/featuretools', 0.6769810914993286, 'ml', 5), ('tensorflow/tensorflow', 0.6535964608192444, 'ml-dl', 5), ('determined-ai/determined', 0.6512665748596191, 'ml-ops', 8), ('epistasislab/tpot', 0.6485167741775513, 'ml', 6), ('alpa-projects/alpa', 0.6484193205833435, 'ml-dl', 2), ('onnx/onnx', 0.6350607872009277, 'ml', 5), ('huggingface/datasets', 0.6315370798110962, 'nlp', 4), ('rafiqhasan/auto-tensorflow', 0.6200402975082397, 'ml-dl', 3), ('xplainable/xplainable', 0.6121291518211365, 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0.5761905312538147, 'study', 3), ('huggingface/autotrain-advanced', 0.5753588080406189, 'ml', 2), ('doccano/doccano', 0.573647141456604, 'nlp', 1), ('explosion/thinc', 0.5728657841682434, 'ml-dl', 4), ('microsoft/deepspeed', 0.5704576373100281, 'ml-dl', 3), ('feast-dev/feast', 0.5683546662330627, 'ml-ops', 3), ('googlecloudplatform/vertex-ai-samples', 0.5683177709579468, 'ml', 2), ('neuralmagic/sparseml', 0.565841555595398, 'ml-dl', 3), ('ludwig-ai/ludwig', 0.5615371465682983, 'ml-ops', 5), ('selfexplainml/piml-toolbox', 0.5612987279891968, 'ml-interpretability', 0), ('tensorflow/tensor2tensor', 0.5608126521110535, 'ml', 2), ('tigerlab-ai/tiger', 0.5559183359146118, 'llm', 0), ('aws/sagemaker-python-sdk', 0.5550652146339417, 'ml', 3), ('titanml/takeoff', 0.5543978214263916, 'llm', 0), ('unionai-oss/unionml', 0.5530210137367249, 'ml-ops', 2), ('merantix-momentum/squirrel-core', 0.5516149401664734, 'ml', 6), ('ddbourgin/numpy-ml', 0.5512529015541077, 'ml', 1), 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1), ('huggingface/exporters', 0.5089559555053711, 'ml', 4), ('optuna/optuna', 0.5085669159889221, 'ml', 3), ('uber/petastorm', 0.508219301700592, 'data', 4), ('oegedijk/explainerdashboard', 0.507343053817749, 'ml-interpretability', 0), ('google/temporian', 0.5072931051254272, 'time-series', 1), ('fmind/mlops-python-package', 0.5072845816612244, 'template', 1), ('oml-team/open-metric-learning', 0.5069662928581238, 'ml', 3), ('towhee-io/towhee', 0.5067926049232483, 'ml-ops', 1), ('kubeflow/katib', 0.5062976479530334, 'ml', 0), ('kevinmusgrave/pytorch-metric-learning', 0.5050148367881775, 'ml', 3), ('mindsdb/mindsdb', 0.5044615864753723, 'data', 1), ('salesforce/merlion', 0.503190279006958, 'time-series', 2), ('intel/scikit-learn-intelex', 0.5030348300933838, 'perf', 2), ('skops-dev/skops', 0.5024822950363159, 'ml-ops', 2), ('horovod/horovod', 0.5024771094322205, 'ml-ops', 4), ('aiqc/aiqc', 0.5022141337394714, 'ml-ops', 0), ('google-research/language', 0.5012085437774658, 'nlp', 1), ('pycaret/pycaret', 0.5001939535140991, 'ml', 2)]

192

3

null

2.71

46

7

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3

2

9

2

46

29

90

0.6

56

106

nlp

https://github.com/nltk/nltk

[]

null

[]

null

nltk/nltk

nltk

12,688

2,824

468

Python

https://www.nltk.org

NLTK Source

nltk

2024-01-13

2009-09-07

751

16.891594

https://avatars.githubusercontent.com/u/124114?v=4

NLTK Source

['machine-learning', 'natural-language-processing', 'nlp', 'nltk']

2023-12-24

[('allenai/allennlp', 0.6935926675796509, 'nlp', 2), ('flairnlp/flair', 0.6725092530250549, 'nlp', 3), ('explosion/spacy-models', 0.6720556020736694, 'nlp', 3), ('explosion/spacy', 0.6628869771957397, 'nlp', 3), ('sloria/textblob', 0.6578431129455566, 'nlp', 3), ('lexpredict/lexpredict-lexnlp', 0.6562715172767639, 'nlp', 1), ('rasahq/rasa', 0.6307575106620789, 'llm', 3), ('keras-team/keras-nlp', 0.6287647485733032, 'nlp', 3), ('alibaba/easynlp', 0.6162857413291931, 'nlp', 2), ('explosion/spacy-llm', 0.6157956123352051, 'llm', 3), ('norskregnesentral/skweak', 0.608248770236969, 'nlp', 1), ('graykode/nlp-tutorial', 0.5764945149421692, 'study', 2), ('makcedward/nlpaug', 0.5745749473571777, 'nlp', 3), ('bigscience-workshop/promptsource', 0.5687624216079712, 'nlp', 3), ('argilla-io/argilla', 0.5657547116279602, 'nlp', 3), ('paddlepaddle/paddlenlp', 0.5588723421096802, 'llm', 1), ('jbesomi/texthero', 0.5517333149909973, 'nlp', 2), ('huggingface/transformers', 0.5491923689842224, 'nlp', 3), ('vi3k6i5/flashtext', 0.5405317544937134, 'data', 1), ('infinitylogesh/mutate', 0.5343964695930481, 'nlp', 0), ('explosion/spacy-streamlit', 0.5315085053443909, 'nlp', 3), ('databrickslabs/dolly', 0.5305935144424438, 'llm', 0), ('gunthercox/chatterbot-corpus', 0.5303866267204285, 'nlp', 0), ('thilinarajapakse/simpletransformers', 0.5254354476928711, 'nlp', 0), ('yueyu1030/attrprompt', 0.5240321755409241, 'llm', 1), ('doccano/doccano', 0.5226835608482361, 'nlp', 2), ('mooler0410/llmspracticalguide', 0.5214924812316895, 'study', 2), ('nvidia/nemo', 0.5199841260910034, 'nlp', 1), ('google-research/language', 0.5192822217941284, 'nlp', 2), ('killianlucas/open-interpreter', 0.5141381621360779, 'llm', 0), ('llmware-ai/llmware', 0.5111628770828247, 'llm', 2), ('huggingface/text-generation-inference', 0.5107032060623169, 'llm', 1), ('franck-dernoncourt/neuroner', 0.5021610856056213, 'nlp', 2), ('rasbt/machine-learning-book', 0.5020496249198914, 'study', 1), ('deepset-ai/farm', 0.5018087029457092, 'nlp', 1), ('explosion/thinc', 0.5009826421737671, 'ml-dl', 3)]

452

6

null

1.58

82

46

175

1

0

3

82

125

90

1.5

56

1,336

llm

https://github.com/blinkdl/rwkv-lm

[]

null

[]

null

blinkdl/rwkv-lm

RWKV-LM

10,652

753

129

Python

null

RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.

blinkdl

2024-01-14

2021-08-08

129

82.39116

null

RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.

['attention-mechanism', 'chatgpt', 'deep-learning', 'gpt', 'gpt-2', 'gpt-3', 'language-model', 'linear-attention', 'lstm', 'pytorch', 'rnn', 'rwkv', 'transformer', 'transformers']

2023-12-28

[('blinkdl/chatrwkv', 0.6400032043457031, 'llm', 5), ('bytedance/lightseq', 0.5059091448783875, 'nlp', 2)]

5

1

null

3.77

34

13

30

1

2

1

34

48

90

1.4

56

366

ml

https://github.com/megvii-basedetection/yolox

[]

null

[]

null

megvii-basedetection/yolox

YOLOX

8,778

2,096

74

Python

null

YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

megvii-basedetection

2024-01-12

2021-07-17

132

66.28479

https://avatars.githubusercontent.com/u/67775453?v=4

YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

['deep-learning', 'megengine', 'ncnn', 'object-detection', 'onnx', 'openvino', 'pytorch', 'tensorrt', 'yolo', 'yolov3', 'yolox']

2023-05-23

[('microsoft/onnxruntime', 0.5817757844924927, 'ml', 3), ('deci-ai/super-gradients', 0.5785552859306335, 'ml-dl', 3), ('open-mmlab/mmdetection', 0.545394778251648, 'ml', 3), ('horovod/horovod', 0.5106202363967896, 'ml-ops', 2), ('neuralmagic/deepsparse', 0.5051378607749939, 'nlp', 2), ('roboflow/supervision', 0.5012127161026001, 'ml', 4)]

74

5

null

0.15

49

13

30

8

0

2

49

46

90

0.9

56

456

perf

https://github.com/nebuly-ai/nebullvm

[]

null

[]

null

nebuly-ai/nebullvm

nebuly

8,331

662

96

Python

https://www.nebuly.com/

The user analytics platform for LLMs

nebuly-ai

2024-01-14

2022-02-12

102

81.334728

https://avatars.githubusercontent.com/u/83510798?v=4

The user analytics platform for LLMs

['ai', 'analytics', 'artificial-intelligence', 'deeplearning', 'large-language-models', 'llm']

2023-10-28

[('pathwaycom/llm-app', 0.6677808165550232, 'llm', 1), ('microsoft/semantic-kernel', 0.6294217705726624, 'llm', 3), ('deepset-ai/haystack', 0.6285997033119202, 'llm', 2), ('tigerlab-ai/tiger', 0.6134838461875916, 'llm', 2), ('mlc-ai/mlc-llm', 0.6126720309257507, 'llm', 1), ('nomic-ai/gpt4all', 0.6061845421791077, 'llm', 0), ('argilla-io/argilla', 0.6039616465568542, 'nlp', 2), ('microsoft/promptflow', 0.5947597622871399, 'llm', 2), ('llmware-ai/llmware', 0.5862234830856323, 'llm', 2), ('microsoft/lmops', 0.5789636373519897, 'llm', 1), ('hegelai/prompttools', 0.5767601132392883, 'llm', 1), ('bigscience-workshop/petals', 0.5763605237007141, 'data', 1), ('night-chen/toolqa', 0.5734456181526184, 'llm', 1), ('intel/intel-extension-for-transformers', 0.5715976357460022, 'perf', 0), ('activeloopai/deeplake', 0.5655378103256226, 'ml-ops', 3), ('iryna-kondr/scikit-llm', 0.5629363059997559, 'llm', 1), ('lancedb/lancedb', 0.5628674030303955, 'data', 0), ('young-geng/easylm', 0.5627244114875793, 'llm', 1), ('microsoft/jarvis', 0.5589395761489868, 'llm', 0), ('paddlepaddle/paddlenlp', 0.556330144405365, 'llm', 1), ('vllm-project/vllm', 0.5560014247894287, 'llm', 1), ('microsoft/autogen', 0.554498553276062, 'llm', 0), ('embedchain/embedchain', 0.5530699491500854, 'llm', 2), ('aimhubio/aim', 0.5485852360725403, 'ml-ops', 1), ('aiwaves-cn/agents', 0.5476635098457336, 'nlp', 1), ('mooler0410/llmspracticalguide', 0.5461376905441284, 'study', 1), ('salesforce/codet5', 0.5400938987731934, 'nlp', 1), ('microsoft/torchscale', 0.5394699573516846, 'llm', 0), ('salesforce/xgen', 0.5392612814903259, 'llm', 2), ('ray-project/ray-llm', 0.5362703800201416, 'llm', 2), ('alphasecio/langchain-examples', 0.5353783369064331, 'llm', 1), ('cheshire-cat-ai/core', 0.5341480374336243, 'llm', 2), ('bobazooba/xllm', 0.5337145328521729, 'llm', 2), ('agenta-ai/agenta', 0.5309828519821167, 'llm', 2), ('explosion/spacy-llm', 0.5306288003921509, 'llm', 2), ('bentoml/openllm', 0.5305408835411072, 'ml-ops', 2), ('mindsdb/mindsdb', 0.529395341873169, 'data', 3), ('titanml/takeoff', 0.5286065936088562, 'llm', 1), ('chatarena/chatarena', 0.5283238887786865, 'llm', 3), ('eleutherai/the-pile', 0.528251588344574, 'data', 1), ('dylanhogg/llmgraph', 0.527693510055542, 'ml', 1), ('ludwig-ai/ludwig', 0.5271685123443604, 'ml-ops', 2), ('confident-ai/deepeval', 0.5270206928253174, 'testing', 1), ('lm-sys/fastchat', 0.5269201993942261, 'llm', 0), ('jina-ai/thinkgpt', 0.5268137454986572, 'llm', 0), ('h2oai/h2o-llmstudio', 0.5265906453132629, 'llm', 2), ('alpha-vllm/llama2-accessory', 0.5258677005767822, 'llm', 0), ('sweepai/sweep', 0.5257266163825989, 'llm', 2), ('eugeneyan/open-llms', 0.5213199257850647, 'study', 2), ('databrickslabs/dolly', 0.5198688507080078, 'llm', 0), ('mlflow/mlflow', 0.5198503136634827, 'ml-ops', 1), ('jerryjliu/llama_index', 0.518968403339386, 'llm', 1), ('determined-ai/determined', 0.5143813490867615, 'ml-ops', 0), ('truera/trulens', 0.5128412842750549, 'llm', 1), ('shishirpatil/gorilla', 0.512731671333313, 'llm', 1), ('salesforce/logai', 0.5123262405395508, 'util', 1), ('googlecloudplatform/vertex-ai-samples', 0.5115224719047546, 'ml', 1), ('superduperdb/superduperdb', 0.5111740827560425, 'data', 1), ('chancefocus/pixiu', 0.5107274651527405, 'finance', 2), ('operand/agency', 0.5101591348648071, 'llm', 3), ('rasahq/rasa', 0.5099035501480103, 'llm', 0), ('arize-ai/phoenix', 0.5097155570983887, 'ml-interpretability', 0), ('nvidia/deeplearningexamples', 0.5064698457717896, 'ml-dl', 1), ('rcgai/simplyretrieve', 0.5062447786331177, 'llm', 2), ('infinitylogesh/mutate', 0.5052860379219055, 'nlp', 0), ('huggingface/datasets', 0.5037619471549988, 'nlp', 0), ('modularml/mojo', 0.5025712847709656, 'util', 1), ('deep-diver/llm-as-chatbot', 0.5001731514930725, 'llm', 0)]

40

5

null

8.1

0

23

3

5

13

5

0

90

0

56

1,034

finance

https://github.com/quantconnect/lean

[]

null

[]

null

quantconnect/lean

Lean

8,317

3,085

415

C#

https://lean.io

Lean Algorithmic Trading Engine by QuantConnect (Python, C#)

quantconnect

2024-01-14

2014-11-28

478

17.378806

https://avatars.githubusercontent.com/u/3912814?v=4

Lean Algorithmic Trading Engine by QuantConnect (Python, C#)

['algorithm', 'algorithmic-trading-engine', 'c-sharp', 'finance', 'forex', 'lean-engine', 'options', 'quantconnect', 'stock-indicators', 'trading', 'trading-algorithms', 'trading-bot', 'trading-platform', 'trading-strategies']

2024-01-11

[('gbeced/pyalgotrade', 0.7084618806838989, 'finance', 0), ('quantopian/zipline', 0.6676159501075745, 'finance', 0), ('ranaroussi/quantstats', 0.6603469848632812, 'finance', 1), ('polakowo/vectorbt', 0.6572080254554749, 'finance', 3), ('goldmansachs/gs-quant', 0.6400971412658691, 'finance', 1), ('zvtvz/zvt', 0.6376045942306519, 'finance', 3), ('gbeced/basana', 0.6268382668495178, 'finance', 1), ('robcarver17/pysystemtrade', 0.6064723134040833, 'finance', 0), ('kernc/backtesting.py', 0.5955772995948792, 'finance', 5), ('idanya/algo-trader', 0.5937037467956543, 'finance', 2), ('freqtrade/freqtrade', 0.5934526324272156, 'crypto', 1), ('polyaxon/datatile', 0.590923011302948, 'pandas', 0), ('cuemacro/finmarketpy', 0.588824987411499, 'finance', 1), ('willmcgugan/textual', 0.5675188899040222, 'term', 0), ('ccxt/ccxt', 0.5551174879074097, 'crypto', 1), ('ai4finance-foundation/finrl', 0.5530506372451782, 'finance', 1), ('ta-lib/ta-lib-python', 0.5490601062774658, 'finance', 1), ('hydrosquall/tiingo-python', 0.5375146865844727, 'finance', 1), ('blankly-finance/blankly', 0.5336184501647949, 'finance', 3), ('plotly/dash', 0.529013454914093, 'viz', 1), ('thealgorithms/python', 0.5260835886001587, 'study', 1), ('google/tf-quant-finance', 0.5243059992790222, 'finance', 1), ('microsoft/qlib', 0.5189212560653687, 'finance', 1), ('kitao/pyxel', 0.5179747343063354, 'gamedev', 0), ('gradio-app/gradio', 0.5162667632102966, 'viz', 0), ('keon/algorithms', 0.512477457523346, 'util', 1), ('online-ml/river', 0.511631429195404, 'ml', 0), ('clips/pattern', 0.5098506808280945, 'nlp', 0), ('1200wd/bitcoinlib', 0.5076516270637512, 'crypto', 0), ('numerai/example-scripts', 0.5045038461685181, 'finance', 0), ('panda3d/panda3d', 0.5038788318634033, 'gamedev', 0), ('explosion/spacy', 0.5002435445785522, 'nlp', 0)]

198

2

null

10.94

236

170

111

0

331

236

127

90

0.5

56

420

ml-dl

https://github.com/pyro-ppl/pyro

[]

null

[]

null

pyro-ppl/pyro

pyro

8,243

985

204

Python

http://pyro.ai

Deep universal probabilistic programming with Python and PyTorch

pyro-ppl

2024-01-13

2017-06-16

345

23.853245

https://avatars.githubusercontent.com/u/46794900?v=4

Deep universal probabilistic programming with Python and PyTorch

['bayesian', 'bayesian-inference', 'deep-learning', 'machine-learning', 'probabilistic-modeling', 'probabilistic-programming', 'pytorch', 'variational-inference']

2024-01-14

[('pymc-devs/pymc3', 0.6964523792266846, 'ml', 3), ('intellabs/bayesian-torch', 0.6956607699394226, 'ml', 3), ('probml/pyprobml', 0.6461431980133057, 'ml', 3), ('pytorch/botorch', 0.6212801933288574, 'ml-dl', 0), ('thu-ml/tianshou', 0.5777061581611633, 'ml-rl', 1), ('huggingface/transformers', 0.5731987953186035, 'nlp', 3), ('rasbt/machine-learning-book', 0.5722088813781738, 'study', 3), ('mrdbourke/pytorch-deep-learning', 0.5717006325721741, 'study', 3), ('denys88/rl_games', 0.558512806892395, 'ml-rl', 2), ('pytorch/ignite', 0.5561047196388245, 'ml-dl', 3), ('keras-team/keras', 0.5552471876144409, 'ml-dl', 3), ('awslabs/gluonts', 0.5475439429283142, 'time-series', 3), ('pytorch/rl', 0.5450016856193542, 'ml-rl', 2), ('ddbourgin/numpy-ml', 0.5446068644523621, 'ml', 2), ('google/trax', 0.539913535118103, 'ml-dl', 2), ('intel/intel-extension-for-pytorch', 0.538422167301178, 'perf', 3), ('tensorlayer/tensorlayer', 0.5288735628128052, 'ml-rl', 1), ('ageron/handson-ml2', 0.522969663143158, 'ml', 0), ('bayesianmodelingandcomputationinpython/bookcode_edition1', 0.5214691162109375, 'study', 0), ('nvidia/deeplearningexamples', 0.5212848782539368, 'ml-dl', 2), ('lukaszahradnik/pyneuralogic', 0.5193347930908203, 'math', 3), ('keras-rl/keras-rl', 0.5166857242584229, 'ml-rl', 1), ('scikit-optimize/scikit-optimize', 0.5141356587409973, 'ml', 1), ('microsoft/deepspeed', 0.5087716579437256, 'ml-dl', 3), ('karpathy/micrograd', 0.5077245831489563, 'study', 0), ('fchollet/deep-learning-with-python-notebooks', 0.5035637617111206, 'study', 0), ('pyg-team/pytorch_geometric', 0.5015919208526611, 'ml-dl', 2), ('uber/orbit', 0.5006424188613892, 'time-series', 4)]

148

5

null

1.27

39

26

80

0

2

5

2

39

51

90

1.3

56

1,260

llm

https://github.com/microsoft/lora

[]

null

[]

null

microsoft/lora

LoRA

7,851

476

58

Python

https://arxiv.org/abs/2106.09685

Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"

microsoft

2024-01-14

2021-06-18

136

57.486402

https://avatars.githubusercontent.com/u/6154722?v=4

Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"

['adaptation', 'deberta', 'deep-learning', 'gpt-2', 'gpt-3', 'language-model', 'lora', 'low-rank', 'pytorch', 'roberta']

2024-01-09

[('hannibal046/awesome-llm', 0.6244948506355286, 'study', 1), ('next-gpt/next-gpt', 0.6170973181724548, 'llm', 0), ('lianjiatech/belle', 0.5939985513687134, 'llm', 1), ('bobazooba/xllm', 0.5789094567298889, 'llm', 2), ('microsoft/autogen', 0.5736963152885437, 'llm', 0), ('hiyouga/llama-efficient-tuning', 0.5733075141906738, 'llm', 2), ('hiyouga/llama-factory', 0.5733075141906738, 'llm', 2), ('yueyu1030/attrprompt', 0.5668091177940369, 'llm', 0), ('togethercomputer/redpajama-data', 0.5614542365074158, 'llm', 0), ('cg123/mergekit', 0.5608856678009033, 'llm', 0), ('ai21labs/lm-evaluation', 0.55837482213974, 'llm', 1), ('infinitylogesh/mutate', 0.5570184588432312, 'nlp', 1), ('freedomintelligence/llmzoo', 0.5567244291305542, 'llm', 1), ('lm-sys/fastchat', 0.5482615828514099, 'llm', 1), ('baichuan-inc/baichuan-13b', 0.5445288419723511, 'llm', 0), ('bigscience-workshop/megatron-deepspeed', 0.5398515462875366, 'llm', 0), ('microsoft/megatron-deepspeed', 0.5398515462875366, 'llm', 0), ('huggingface/text-generation-inference', 0.5352991223335266, 'llm', 2), ('extreme-bert/extreme-bert', 0.5327245593070984, 'llm', 3), ('salesforce/blip', 0.52529376745224, 'diffusion', 0), ('eleutherai/lm-evaluation-harness', 0.5240524411201477, 'llm', 1), ('fasteval/fasteval', 0.5221768021583557, 'llm', 0), ('lupantech/chameleon-llm', 0.5212894082069397, 'llm', 1), ('openai/finetune-transformer-lm', 0.520248532295227, 'llm', 0), ('young-geng/easylm', 0.519779622554779, 'llm', 2), ('databrickslabs/dolly', 0.5188591480255127, 'llm', 0), ('sjtu-ipads/powerinfer', 0.5186458230018616, 'llm', 0), ('juncongmoo/pyllama', 0.5170261263847351, 'llm', 0), ('nvlabs/prismer', 0.5161336064338684, 'diffusion', 1), ('oobabooga/text-generation-webui', 0.5137597918510437, 'llm', 1), ('lightning-ai/lit-llama', 0.5121870040893555, 'llm', 1), ('huggingface/transformers', 0.5106838941574097, 'nlp', 3), ('xtekky/gpt4free', 0.5105166435241699, 'llm', 2), ('thudm/chatglm2-6b', 0.5071834921836853, 'llm', 0), ('ggerganov/ggml', 0.5070888996124268, 'ml', 0), ('bytedance/lightseq', 0.5001585483551025, 'nlp', 0)]

12

3

null

0.37

26

7

31

0

2

26

31

90

1.2

56

469

gui

https://github.com/parthjadhav/tkinter-designer

[]

null

[]

null

parthjadhav/tkinter-designer

Tkinter-Designer

7,773

742

78

Python

null

An easy and fast way to create a Python GUI 🐍

parthjadhav

2024-01-14

2021-05-18

141

55.12766

null

An easy and fast way to create a Python GUI 🐍

['automatic', 'collaborate', 'drag-and-drop', 'easy', 'easy-to-use', 'fast', 'figma', 'gui', 'gui-application', 'learn', 'python-script', 'tkinter', 'tkinter-designer', 'tkinter-graphic-interface', 'tkinter-gui', 'tkinter-python', 'tkinter-widgets']

2024-01-04

[('pysimplegui/pysimplegui', 0.7242632508277893, 'gui', 4), ('hoffstadt/dearpygui', 0.6940200924873352, 'gui', 1), ('r0x0r/pywebview', 0.6899272799491882, 'gui', 1), ('beeware/toga', 0.6891065239906311, 'gui', 1), ('willmcgugan/textual', 0.5848771333694458, 'term', 0), ('wxwidgets/phoenix', 0.58327716588974, 'gui', 1), ('holoviz/panel', 0.5603848099708557, 'viz', 1), ('kivy/kivy', 0.554401695728302, 'util', 0), ('urwid/urwid', 0.5480352640151978, 'term', 0), ('adamerose/pandasgui', 0.5451450943946838, 'pandas', 1), ('holoviz/holoviz', 0.5346206426620483, 'viz', 0), ('pyglet/pyglet', 0.5310909748077393, 'gamedev', 0), ('jquast/blessed', 0.5266092419624329, 'term', 0), ('tkrabel/bamboolib', 0.5206194519996643, 'pandas', 0), ('matplotlib/matplotlib', 0.5160230398178101, 'viz', 0), ('bokeh/bokeh', 0.5127165913581848, 'viz', 0), ('pypy/pypy', 0.5007215738296509, 'util', 0)]

45

2

null

0.23

39

10

32

0

1

3

1

39

59

90

1.5

56

923

ml-rl

https://github.com/lucidrains/palm-rlhf-pytorch

[]

null

[]

null

lucidrains/palm-rlhf-pytorch

PaLM-rlhf-pytorch

7,494

649

139

Python

null

Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM

lucidrains

2024-01-12

2022-12-09

59

125.798561

null

Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM

['artificial-intelligence', 'attention-mechanisms', 'deep-learning', 'human-feedback', 'reinforcement-learning', 'transformers']

2023-04-05

[('denys88/rl_games', 0.5653679370880127, 'ml-rl', 2), ('deepmind/android_env', 0.5164604187011719, 'ml-dl', 1)]

5

3

null

0.58

4

2

13

9

15

65

15

4

90

1

56

960

ml-rl

https://github.com/thu-ml/tianshou

[]

null

[]

null

thu-ml/tianshou

tianshou

7,086

1,071

90

Python

https://tianshou.readthedocs.io

An elegant PyTorch deep reinforcement learning library.

thu-ml

2024-01-12

2018-04-16

302

23.452482

https://avatars.githubusercontent.com/u/19198992?v=4

An elegant PyTorch deep reinforcement learning library.

['a2c', 'atari', 'bcq', 'benchmark', 'cql', 'ddpg', 'double-dqn', 'dqn', 'drl', 'imitation-learning', 'mujoco', 'npg', 'policy-gradient', 'ppo', 'pytorch', 'rl', 'sac', 'td3', 'trpo']

2024-01-12

[('denys88/rl_games', 0.7549825310707092, 'ml-rl', 1), ('pytorch/rl', 0.7527033090591431, 'ml-rl', 2), ('humancompatibleai/imitation', 0.7333576679229736, 'ml-rl', 1), ('openai/baselines', 0.6823237538337708, 'ml-rl', 0), ('salesforce/warp-drive', 0.6808977723121643, 'ml-rl', 1), ('tensorlayer/tensorlayer', 0.6603164076805115, 'ml-rl', 1), ('keras-rl/keras-rl', 0.6519415378570557, 'ml-rl', 0), ('kzl/decision-transformer', 0.6393781900405884, 'ml-rl', 1), ('google/trax', 0.625861406326294, 'ml-dl', 0), ('google/dopamine', 0.6199951171875, 'ml-rl', 1), ('pytorch/ignite', 0.6126653552055359, 'ml-dl', 1), ('mrdbourke/pytorch-deep-learning', 0.5997803211212158, 'study', 1), ('unity-technologies/ml-agents', 0.598300576210022, 'ml-rl', 0), ('openai/spinningup', 0.5972070097923279, 'study', 0), ('karpathy/micrograd', 0.5894965529441833, 'study', 0), ('deepmind/acme', 0.5823108553886414, 'ml-rl', 0), ('pyro-ppl/pyro', 0.5777061581611633, 'ml-dl', 1), ('openai/gym', 0.5749742984771729, 'ml-rl', 0), ('ai4finance-foundation/finrl', 0.5749337673187256, 'finance', 0), ('inspirai/timechamber', 0.5735207796096802, 'sim', 0), ('farama-foundation/gymnasium', 0.57296222448349, 'ml-rl', 0), ('tensorflow/tensor2tensor', 0.5683255791664124, 'ml', 0), ('shangtongzhang/reinforcement-learning-an-introduction', 0.5635957717895508, 'study', 0), ('facebookresearch/habitat-lab', 0.5616220831871033, 'sim', 0), ('pettingzoo-team/pettingzoo', 0.556010365486145, 'ml-rl', 0), ('intel/intel-extension-for-pytorch', 0.5456005930900574, 'perf', 1), ('skorch-dev/skorch', 0.5379747152328491, 'ml-dl', 1), ('nvidia-omniverse/isaacgymenvs', 0.5374286770820618, 'sim', 0), ('facebookresearch/reagent', 0.5355173945426941, 'ml-rl', 0), ('intellabs/bayesian-torch', 0.5311893820762634, 'ml', 1), ('deepmind/dm_control', 0.5307285189628601, 'ml-rl', 1), ('nvidia-omniverse/omniisaacgymenvs', 0.5271867513656616, 'sim', 0), ('arise-initiative/robosuite', 0.5250179171562195, 'ml-rl', 0), ('facebookresearch/pytorch3d', 0.5248837471008301, 'ml-dl', 0), ('nvidia/apex', 0.5245383381843567, 'ml-dl', 0), ('facebookresearch/theseus', 0.5228813886642456, 'math', 1), ('rasbt/machine-learning-book', 0.5220516920089722, 'study', 1), ('pyg-team/pytorch_geometric', 0.5205722451210022, 'ml-dl', 1), ('d2l-ai/d2l-en', 0.5155929923057556, 'study', 1), ('huggingface/transformers', 0.5113345980644226, 'nlp', 1), ('allenai/allennlp', 0.5055130124092102, 'nlp', 1), ('huggingface/deep-rl-class', 0.5006495714187622, 'study', 0)]

65

4

null

4.12

77

37

70

0

1

5

1

77

155

90

2

56

717

ml

https://github.com/py-why/dowhy

[]

null

[]

null

py-why/dowhy

dowhy

6,454

883

137

Python

https://www.pywhy.org/dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

py-why

2024-01-13

2018-05-31

295

21.825121

https://avatars.githubusercontent.com/u/101266056?v=4

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

['bayesian-networks', 'causal-inference', 'causal-machine-learning', 'causal-models', 'causality', 'data-science', 'do-calculus', 'graphical-models', 'machine-learning', 'treatment-effects']

2024-01-08

[('mckinsey/causalnex', 0.7358757853507996, 'math', 5), ('willianfuks/tfcausalimpact', 0.6020914912223816, 'math', 1), ('py-why/econml', 0.5789477229118347, 'ml', 4), ('eleutherai/pyfra', 0.5379133820533752, 'ml', 0), ('quantecon/quantecon.py', 0.513481080532074, 'sim', 0)]

82

5

null

3.46

119

107

68

0

4

3

4

119

102

90

0.9

56

278

jupyter

https://github.com/nteract/papermill

[]

null

[]

null

nteract/papermill

papermill

5,497

409

93

Python

http://papermill.readthedocs.io/en/latest/

📚 Parameterize, execute, and analyze notebooks

nteract

2024-01-14

2017-07-06

342

16.0396

https://avatars.githubusercontent.com/u/12401040?v=4

📚 Parameterize, execute, and analyze notebooks

['julia', 'jupyter', 'notebook', 'notebook-generator', 'notebooks', 'nteract', 'pipeline', 'publishing', 'r', 'scala']

2024-01-01

[('mwouts/jupytext', 0.632023811340332, 'jupyter', 1), ('jupyter/nbformat', 0.618989109992981, 'jupyter', 0), ('cohere-ai/notebooks', 0.5747708082199097, 'llm', 1), ('jupyter/notebook', 0.5524148344993591, 'jupyter', 2), ('aws/graph-notebook', 0.5402319431304932, 'jupyter', 1), ('linealabs/lineapy', 0.5371261835098267, 'jupyter', 0), ('ploomber/ploomber', 0.5353273153305054, 'ml-ops', 2), ('jupyter/nbgrader', 0.532752513885498, 'jupyter', 1), ('jupyter/nbconvert', 0.5243469476699829, 'jupyter', 0), ('quantopian/qgrid', 0.516223669052124, 'jupyter', 0), ('fchollet/deep-learning-with-python-notebooks', 0.5121607780456543, 'study', 0), ('malloydata/malloy-py', 0.5121511220932007, 'data', 0), ('jupyter/nbdime', 0.5114229917526245, 'jupyter', 1), ('pytoolz/toolz', 0.5096691250801086, 'util', 0), ('jupyter-widgets/ipywidgets', 0.5082428455352783, 'jupyter', 0), ('fluentpython/example-code-2e', 0.5064553022384644, 'study', 0), ('kellyjonbrazil/jc', 0.5040388703346252, 'util', 0), ('fastai/fastcore', 0.5034418106079102, 'util', 0), ('jupyter-lsp/jupyterlab-lsp', 0.5029893517494202, 'jupyter', 3)]

114

7

null

0.69

51

40

79

0

12

51

86

90

1.7

56

361

ml-ops

https://github.com/allegroai/clearml

[]

null

[]

null

allegroai/clearml

clearml

4,979

626

91

Python

https://clear.ml/docs

ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management

allegroai

2024-01-14

2019-06-10

242

20.562242

https://avatars.githubusercontent.com/u/38647316?v=4

ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management

['ai', 'clearml', 'control', 'deep-learning', 'deeplearning', 'devops', 'experiment', 'experiment-manager', 'k8s', 'machine-learning', 'machinelearning', 'mlops', 'trains', 'trainsai', 'version', 'version-control']

2024-01-12

[('zenml-io/zenml', 0.66759192943573, 'ml-ops', 4), ('polyaxon/polyaxon', 0.6574744582176208, 'ml-ops', 4), ('iterative/dvc', 0.618588924407959, 'ml-ops', 2), ('bodywork-ml/bodywork-core', 0.6049355268478394, 'ml-ops', 3), ('netflix/metaflow', 0.5861303210258484, 'ml-ops', 3), ('fmind/mlops-python-package', 0.5833768844604492, 'template', 2), ('getindata/kedro-kubeflow', 0.5791431069374084, 'ml-ops', 2), ('bentoml/bentoml', 0.5609636902809143, 'ml-ops', 4), ('kubeflow/pipelines', 0.5604597330093384, 'ml-ops', 2), ('orchest/orchest', 0.5581900477409363, 'ml-ops', 1), ('ploomber/ploomber', 0.5556386113166809, 'ml-ops', 2), ('avaiga/taipy', 0.5540127158164978, 'data', 1), ('flyteorg/flyte', 0.5446012616157532, 'ml-ops', 2), ('tox-dev/tox', 0.5439307689666748, 'testing', 0), ('mage-ai/mage-ai', 0.5418257713317871, 'ml-ops', 1), ('kestra-io/kestra', 0.5374925136566162, 'ml-ops', 0), ('unionai-oss/unionml', 0.536503255367279, 'ml-ops', 2), ('microsoft/nni', 0.5334336757659912, 'ml', 3), ('lastmile-ai/aiconfig', 0.5247846841812134, 'util', 1), ('wandb/client', 0.5239328742027283, 'ml', 3), ('prefecthq/prefect', 0.5174835324287415, 'ml-ops', 0)]

88

3

null

2.83

74

21

56

0

18

34

18

74

141

90

1.9

56

1,371

llm

https://github.com/minedojo/voyager

[]

null

[]

null

minedojo/voyager

Voyager

4,708

445

60

JavaScript

https://voyager.minedojo.org/

An Open-Ended Embodied Agent with Large Language Models

minedojo

2024-01-14

2023-05-25

35

131.824

https://avatars.githubusercontent.com/u/98871221?v=4

An Open-Ended Embodied Agent with Large Language Models

['embodied-learning', 'large-language-models', 'minecraft', 'open-ended-learning']

2023-07-27

[('facebookresearch/droidlet', 0.6723781228065491, 'sim', 0), ('facebookresearch/habitat-lab', 0.6467283964157104, 'sim', 0), ('aiwaves-cn/agents', 0.5751522183418274, 'nlp', 0), ('jina-ai/thinkgpt', 0.5710037350654602, 'llm', 0), ('humanoidagents/humanoidagents', 0.56615149974823, 'sim', 0), ('lm-sys/fastchat', 0.5574104189872742, 'llm', 0), ('luodian/otter', 0.5513647794723511, 'llm', 0), ('inspirai/timechamber', 0.5301423072814941, 'sim', 0), ('lupantech/chameleon-llm', 0.5282621383666992, 'llm', 0), ('operand/agency', 0.516743540763855, 'llm', 0), ('ctlllll/llm-toolmaker', 0.5137326121330261, 'llm', 0), ('next-gpt/next-gpt', 0.509900689125061, 'llm', 1)]

13

4

null

0.42

23

16

8

6

0

23

25

90

1.1

56

375

util

https://github.com/spotify/pedalboard

[]

null

[]

null

spotify/pedalboard

pedalboard

4,677

219

56

C++

https://spotify.github.io/pedalboard/

🎛 🔊 A Python library for working with audio.

spotify

2024-01-13

2021-07-06

134

34.902985

https://avatars.githubusercontent.com/u/251374?v=4

🎛 🔊 A Python library for working with audio.

['audio', 'audio-processing', 'audio-production', 'audio-research', 'audio-unit', 'juce', 'pybind11', 'tensorflow', 'vst3', 'vst3-host']

2023-12-14

[('bastibe/python-soundfile', 0.7314440608024597, 'util', 0), ('irmen/pyminiaudio', 0.7280553579330444, 'util', 0), ('uberi/speech_recognition', 0.6759282946586609, 'ml', 1), ('taylorsmarks/playsound', 0.6269357204437256, 'util', 0), ('libaudioflux/audioflux', 0.5974409580230713, 'util', 2), ('speechbrain/speechbrain', 0.5878923535346985, 'nlp', 2), ('quodlibet/mutagen', 0.5746901035308838, 'util', 0), ('nateshmbhat/pyttsx3', 0.5451530814170837, 'util', 0), ('pndurette/gtts', 0.5376996994018555, 'util', 0), ('pytoolz/toolz', 0.5321218371391296, 'util', 0), ('jamesturk/jellyfish', 0.5257704854011536, 'nlp', 0), ('facebookresearch/audiocraft', 0.5256170034408569, 'util', 1), ('espnet/espnet', 0.5202059745788574, 'nlp', 0), ('pypy/pypy', 0.5107285976409912, 'util', 0), ('googleapis/python-speech', 0.5077892541885376, 'ml', 0)]

27

5

null

2.19

35

13

31

1

20

22

20

35

42

90

1.2

56

1,452

util

https://github.com/conda-forge/miniforge

[]

null

[]

null

conda-forge/miniforge

miniforge

4,654

266

50

Shell

https://conda-forge.org/miniforge

A conda-forge distribution.

conda-forge

2024-01-14

2019-11-14

219

21.182055

https://avatars.githubusercontent.com/u/11897326?v=4

A conda-forge distribution.

[]

2023-12-21

[('conda/conda-pack', 0.5824256539344788, 'util', 0), ('mamba-org/quetz', 0.5642527341842651, 'util', 0), ('conda-forge/feedstocks', 0.5309390425682068, 'util', 0), ('mamba-org/boa', 0.5230752825737, 'util', 0)]

37

5

null

1.42

59

30

51

1

15

19

15

59

143

90

2.4

56

347

ml-ops

https://github.com/evidentlyai/evidently

[]

null

[]

null

evidentlyai/evidently

evidently

4,312

477

43

Jupyter Notebook

null

Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b

evidentlyai

2024-01-12

2020-11-25

165

25.998277

https://avatars.githubusercontent.com/u/75031056?v=4

Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b

['data-drift', 'data-science', 'html-report', 'jupyter-notebook', 'machine-learning', 'machine-learning-operations', 'mlops', 'model-monitoring', 'pandas-dataframe', 'production-machine-learning']

2024-01-12

[('deepchecks/deepchecks', 0.6157994866371155, 'data', 8), ('fmind/mlops-python-package', 0.5556315779685974, 'template', 1), ('selfexplainml/piml-toolbox', 0.5544941425323486, 'ml-interpretability', 0), ('huggingface/evaluate', 0.5467391014099121, 'ml', 1), ('kubeflow/fairing', 0.531782329082489, 'ml-ops', 0), ('districtdatalabs/yellowbrick', 0.531039834022522, 'ml', 1), ('polyaxon/polyaxon', 0.5295282006263733, 'ml-ops', 3), ('arize-ai/phoenix', 0.5009012818336487, 'ml-interpretability', 2)]

57

3

null

6.9

148

121

38

0

25

21

25

148

76

90

0.5

56

826

util

https://github.com/adafruit/circuitpython

[]

null

[]

null

adafruit/circuitpython

circuitpython

3,787

1,073

128

C

https://circuitpython.org

CircuitPython - a Python implementation for teaching coding with microcontrollers

adafruit

2024-01-13

2016-08-20

388

9.74954

https://avatars.githubusercontent.com/u/181069?v=4

CircuitPython - a Python implementation for teaching coding with microcontrollers

['beginner', 'circuitpython', 'cpython', 'education', 'embedded', 'microcontroller', 'micropython']

2024-01-13

[('micropython/micropython', 0.7091054916381836, 'util', 3), ('python/cpython', 0.6647933125495911, 'util', 1), ('fchollet/deep-learning-with-python-notebooks', 0.6453861594200134, 'study', 0), ('pypy/pypy', 0.6234596371650696, 'util', 1), ('pyston/pyston', 0.5873665809631348, 'util', 0), ('norvig/pytudes', 0.5722380876541138, 'util', 0), ('ipython/ipyparallel', 0.5501038432121277, 'perf', 0), ('sympy/sympy', 0.5332902669906616, 'math', 0), ('cohere-ai/notebooks', 0.5329226851463318, 'llm', 0), ('jeshraghian/snntorch', 0.5297858119010925, 'ml-dl', 0), ('masoniteframework/masonite', 0.5271365642547607, 'web', 0), ('ageron/handson-ml2', 0.5219725966453552, 'ml', 0), ('cython/cython', 0.5219005346298218, 'util', 1), ('1200wd/bitcoinlib', 0.519145131111145, 'crypto', 0), ('primal100/pybitcointools', 0.518639862537384, 'crypto', 0), ('intel/intel-extension-for-pytorch', 0.5163028240203857, 'perf', 0), ('r0x0r/pywebview', 0.5162983536720276, 'gui', 0), ('brandtbucher/specialist', 0.5155614018440247, 'perf', 1), ('eleutherai/pyfra', 0.5133049488067627, 'ml', 0), ('hoffstadt/dearpygui', 0.511806309223175, 'gui', 0), ('imageio/imageio', 0.506452739238739, 'util', 0), ('faster-cpython/tools', 0.5050845742225647, 'perf', 1), ('rasbt/machine-learning-book', 0.5035032033920288, 'study', 0), ('fastai/fastcore', 0.5033023953437805, 'util', 0), ('mynameisfiber/high_performance_python_2e', 0.5031493902206421, 'study', 0), ('joblib/joblib', 0.5005473494529724, 'util', 0)]

1,121

4

null

0

538

356

90

0

30

37

30

537

1,228

90

2.3

56

918

study

https://github.com/roboflow/notebooks

[]

null

[]

null

roboflow/notebooks

notebooks

3,584

553

54

Jupyter Notebook

https://roboflow.com/models

Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.

roboflow

2024-01-13

2022-11-18

62

57.278539

https://avatars.githubusercontent.com/u/53104118?v=4

Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.

['amazon-sagemaker-lab', 'automatic-labeling-system', 'computer-vision', 'deep-learning', 'deep-neural-networks', 'google-colab', 'image-classification', 'image-segmentation', 'machine-learning', 'object-detection', 'open-vocabulary-detection', 'open-vocabulary-segmentation', 'pytorch', 'tutorial', 'yolov5', 'yolov6', 'yolov7', 'yolov8', 'zero-shot-classification', 'zero-shot-detection']

2024-01-10

[('deci-ai/super-gradients', 0.8082399368286133, 'ml-dl', 5), ('roboflow/supervision', 0.6496574878692627, 'ml', 5), ('lucidrains/vit-pytorch', 0.6355553865432739, 'ml-dl', 2), ('idea-research/grounded-segment-anything', 0.6104524731636047, 'llm', 3), ('google-research/maxvit', 0.5931783318519592, 'ml', 2), ('facebookresearch/vissl', 0.5875295996665955, 'ml', 0), ('idea-research/groundingdino', 0.5870379209518433, 'diffusion', 1), ('nvlabs/gcvit', 0.5799825191497803, 'diffusion', 2), ('blakeblackshear/frigate', 0.5778411626815796, 'util', 1), ('rwightman/pytorch-image-models', 0.5683378577232361, 'ml-dl', 1), ('open-mmlab/mmdetection', 0.5606690049171448, 'ml', 2), ('matterport/mask_rcnn', 0.5560668706893921, 'ml-dl', 1), ('microsoft/torchgeo', 0.5472760200500488, 'gis', 3), ('ludwig-ai/ludwig', 0.5439817309379578, 'ml-ops', 4), ('christoschristofidis/awesome-deep-learning', 0.5378063917160034, 'study', 2), ('kornia/kornia', 0.5266382098197937, 'ml-dl', 4), ('salesforce/blip', 0.523171603679657, 'diffusion', 0), ('nyandwi/modernconvnets', 0.5212321877479553, 'ml-dl', 2), ('neuralmagic/sparseml', 0.5195624828338623, 'ml-dl', 3), ('open-mmlab/mmediting', 0.5162927508354187, 'ml', 3), ('datasystemslab/geotorch', 0.5124086141586304, 'gis', 2), ('towhee-io/towhee', 0.511427640914917, 'ml-ops', 2), ('facebookresearch/segment-anything', 0.51060950756073, 'ml-dl', 1), ('sanster/lama-cleaner', 0.5101523995399475, 'ml-dl', 1), ('mosaicml/composer', 0.5099112391471863, 'ml-dl', 3)]

21

3

null

2.79

33

16

14

0

1

32

33

90

1

56

878

study

https://github.com/huggingface/deep-rl-class

[]

null

[]

null

huggingface/deep-rl-class

deep-rl-class

3,426

510

86

MDX

null

This repo contains the syllabus of the Hugging Face Deep Reinforcement Learning Course.

huggingface

2024-01-13

2022-04-21

92

36.952234

https://avatars.githubusercontent.com/u/25720743?v=4

This repo contains the syllabus of the Hugging Face Deep Reinforcement Learning Course.

['deep-learning', 'deep-reinforcement-learning', 'reinforcement-learning', 'reinforcement-learning-excercises']

2024-01-02

[('openai/spinningup', 0.5750541090965271, 'study', 0), ('huggingface/huggingface_hub', 0.5541204810142517, 'ml', 1), ('huggingface/diffusion-models-class', 0.551882803440094, 'study', 0), ('tensorlayer/tensorlayer', 0.5484325885772705, 'ml-rl', 2), ('farama-foundation/gymnasium', 0.5383160710334778, 'ml-rl', 1), ('nvidia-omniverse/isaacgymenvs', 0.534843921661377, 'sim', 0), ('keras-rl/keras-rl', 0.5257301926612854, 'ml-rl', 1), ('pettingzoo-team/pettingzoo', 0.5236347317695618, 'ml-rl', 1), ('facebookresearch/habitat-lab', 0.5081996917724609, 'sim', 3), ('thu-ml/tianshou', 0.5006495714187622, 'ml-rl', 0)]

86

3

null

6.08

64

37

21

0

64

122

90

1.9

56

362

ml-ops

https://github.com/kubeflow/pipelines

[]

null

[]

null

kubeflow/pipelines

pipelines

3,364

1,513

104

Python

https://www.kubeflow.org/docs/components/pipelines/

Machine Learning Pipelines for Kubeflow

kubeflow

2024-01-13

2018-05-12

298

11.272379

https://avatars.githubusercontent.com/u/33164907?v=4

Machine Learning Pipelines for Kubeflow

['data-science', 'kubeflow', 'kubeflow-pipelines', 'kubernetes', 'machine-learning', 'mlops', 'pipeline']

2024-01-12

[('bodywork-ml/bodywork-core', 0.8104010820388794, 'ml-ops', 5), ('getindata/kedro-kubeflow', 0.7283107042312622, 'ml-ops', 3), ('polyaxon/polyaxon', 0.7241019010543823, 'ml-ops', 4), ('kubeflow-kale/kale', 0.692866325378418, 'ml-ops', 3), ('orchest/orchest', 0.6418040990829468, 'ml-ops', 3), ('feast-dev/feast', 0.6390533447265625, 'ml-ops', 3), ('flyteorg/flyte', 0.6268972754478455, 'ml-ops', 4), ('mage-ai/mage-ai', 0.622243344783783, 'ml-ops', 3), ('bentoml/bentoml', 0.6110785603523254, 'ml-ops', 3), ('unionai-oss/unionml', 0.6105091571807861, 'ml-ops', 2), ('netflix/metaflow', 0.5999767184257507, 'ml-ops', 4), ('mlflow/mlflow', 0.5984587669372559, 'ml-ops', 1), ('onnx/onnx', 0.5777002573013306, 'ml', 1), ('ploomber/ploomber', 0.568588137626648, 'ml-ops', 3), ('allegroai/clearml', 0.5604597330093384, 'ml-ops', 2), ('determined-ai/determined', 0.5401206016540527, 'ml-ops', 4), ('koaning/scikit-lego', 0.539598822593689, 'ml', 1), ('microsoft/nni', 0.5366452932357788, 'ml', 3), ('dgarnitz/vectorflow', 0.5347921252250671, 'data', 1), ('zenml-io/zenml', 0.5281010866165161, 'ml-ops', 3), ('tensorflow/tensorflow', 0.5275462865829468, 'ml-dl', 1), ('keras-team/keras-nlp', 0.5210731625556946, 'nlp', 1), ('firmai/industry-machine-learning', 0.5197041034698486, 'study', 2), ('automl/auto-sklearn', 0.5186381936073303, 'ml', 0), ('googlecloudplatform/vertex-ai-samples', 0.5168536901473999, 'ml', 2), ('apache/airflow', 0.5132193565368652, 'ml-ops', 3), ('huggingface/datasets', 0.511340856552124, 'nlp', 1), ('whylabs/whylogs', 0.5075204372406006, 'util', 3), ('gefyrahq/gefyra', 0.5056382417678833, 'util', 1), ('nccr-itmo/fedot', 0.5040023922920227, 'ml-ops', 1), ('xplainable/xplainable', 0.5017673969268799, 'ml-interpretability', 2), ('alirezadir/machine-learning-interview-enlightener', 0.5008544921875, 'study', 1)]

386

1

null

18.08

597

336

69

0

31

28

31

596

1,212

90

2

56

728

data

https://github.com/ibis-project/ibis

[]

null

[]

1

null

ibis-project/ibis

ibis

3,364

466

80

Python

https://ibis-project.org

The flexibility of Python with the scale and performance of modern SQL.

ibis-project

2024-01-14

2015-04-17

458

7.335826

https://avatars.githubusercontent.com/u/27442526?v=4

The flexibility of Python with the scale and performance of modern SQL.

['bigquery', 'clickhouse', 'dask', 'database', 'datafusion', 'duckdb', 'impala', 'mssql', 'mysql', 'pandas', 'polars', 'postgresql', 'pyarrow', 'pyspark', 'snowflake', 'sql', 'sqlalchemy', 'sqlite', 'trino']

2024-01-13

[('tiangolo/sqlmodel', 0.8095237612724304, 'data', 2), ('tobymao/sqlglot', 0.7856696248054504, 'data', 8), ('sqlalchemy/sqlalchemy', 0.741746723651886, 'data', 2), ('kayak/pypika', 0.6313249468803406, 'data', 1), ('machow/siuba', 0.6308576464653015, 'pandas', 2), ('mcfunley/pugsql', 0.6264197826385498, 'data', 1), ('macbre/sql-metadata', 0.6164320707321167, 'data', 2), ('vaexio/vaex', 0.6082955598831177, 'perf', 1), ('andialbrecht/sqlparse', 0.6058615446090698, 'data', 0), ('fugue-project/fugue', 0.5997548699378967, 'pandas', 4), ('malloydata/malloy-py', 0.5992289185523987, 'data', 1), ('datafold/data-diff', 0.5967792272567749, 'data', 6), ('coleifer/peewee', 0.5938148498535156, 'data', 1), ('pytables/pytables', 0.5871632695198059, 'data', 0), ('sfu-db/connector-x', 0.5806707143783569, 'data', 2), ('krzjoa/awesome-python-data-science', 0.5760530233383179, 'study', 0), ('pandas-dev/pandas', 0.5663455724716187, 'pandas', 1), ('fastai/fastcore', 0.566156804561615, 'util', 0), ('aws/aws-sdk-pandas', 0.563861608505249, 'pandas', 2), ('plotly/dash', 0.5618459582328796, 'viz', 0), ('cython/cython', 0.553461492061615, 'util', 0), ('eleutherai/pyfra', 0.5528563857078552, 'ml', 0), ('sqlalchemy/alembic', 0.5510525107383728, 'data', 2), ('pola-rs/polars', 0.5494480729103088, 'pandas', 1), ('airbytehq/airbyte', 0.5454192161560059, 'data', 5), ('collerek/ormar', 0.5441567301750183, 'data', 1), ('simonw/sqlite-utils', 0.540537416934967, 'data', 1), ('dylanhogg/awesome-python', 0.5329792499542236, 'study', 1), ('holoviz/panel', 0.5315485596656799, 'viz', 0), ('apache/spark', 0.5312047004699707, 'data', 1), ('falconry/falcon', 0.5278680324554443, 'web', 0), ('unionai-oss/pandera', 0.525162398815155, 'pandas', 1), ('pyston/pyston', 0.5222876667976379, 'util', 0), ('jina-ai/vectordb', 0.5219907760620117, 'data', 0), ('saulpw/visidata', 0.5209618210792542, 'term', 2), ('hi-primus/optimus', 0.5208921432495117, 'ml-ops', 2), ('googleapis/python-bigquery', 0.5185703635215759, 'data', 0), ('aminalaee/sqladmin', 0.512384831905365, 'data', 1), ('pytoolz/toolz', 0.5118052363395691, 'util', 0), ('python-cachier/cachier', 0.5115165710449219, 'perf', 0), ('aio-libs/aiopg', 0.5114596486091614, 'data', 2), ('aio-libs/aiomysql', 0.5113950967788696, 'data', 2), ('tconbeer/harlequin', 0.5111363530158997, 'term', 1), ('mause/duckdb_engine', 0.5086135864257812, 'data', 3), ('strawberry-graphql/strawberry', 0.5083762407302856, 'web', 0), ('dagworks-inc/hamilton', 0.5063190460205078, 'ml-ops', 1), ('rawheel/fastapi-boilerplate', 0.502396821975708, 'web', 2), ('geopandas/geopandas', 0.5019082427024841, 'gis', 1), ('pyparsing/pyparsing', 0.5017038583755493, 'util', 0), ('klen/muffin', 0.5011864900588989, 'web', 0), ('pypy/pypy', 0.5000938177108765, 'util', 0)]

165

4

null

55.63

674

586

106

0

9

5

9

673

1,004

90

1.5

56

870

time-series

https://github.com/nixtla/statsforecast

[]

null

[]

null

nixtla/statsforecast

statsforecast

3,316

223

31

Python

https://nixtlaverse.nixtla.io/statsforecast

Lightning ⚡️ fast forecasting with statistical and econometric models.

nixtla

2024-01-14

2021-11-24

113

29.124216

https://avatars.githubusercontent.com/u/79945230?v=4

Lightning ⚡️ fast forecasting with statistical and econometric models.

['arima', 'automl', 'baselines', 'data-science', 'econometrics', 'ets', 'exponential-smoothing', 'fbprophet', 'forecasting', 'machine-learning', 'mstl', 'naive', 'neuralprophet', 'predictions', 'prophet', 'seasonal-naive', 'statistics', 'theta', 'time-series']

2024-01-12

[('ourownstory/neural_prophet', 0.6677179336547852, 'ml', 6), ('winedarksea/autots', 0.6360719799995422, 'time-series', 4), ('linkedin/greykite', 0.5983828902244568, 'ml', 0), ('facebook/prophet', 0.586733341217041, 'time-series', 2), ('alkaline-ml/pmdarima', 0.5763822197914124, 'time-series', 5), ('firmai/atspy', 0.5731773972511292, 'time-series', 2), ('autoviml/auto_ts', 0.5572653412818909, 'time-series', 4), ('sktime/sktime', 0.5418822169303894, 'time-series', 4), ('awslabs/autogluon', 0.5410817265510559, 'ml', 5), ('salesforce/merlion', 0.5316644906997681, 'time-series', 4), ('uber/orbit', 0.5311532020568848, 'time-series', 5), ('salesforce/deeptime', 0.5292312502861023, 'time-series', 2), ('microsoft/flaml', 0.5162665843963623, 'ml', 3), ('awslabs/gluonts', 0.5115534067153931, 'time-series', 4), ('aistream-peelout/flow-forecast', 0.506076991558075, 'time-series', 2)]

35

3

null

3.21

126

102

26

0

4

14

4

126

183

90

1.5

56

595

gis

https://github.com/giswqs/geemap

[]

null

[]

null

giswqs/geemap

geemap

3,049

1,042

116

Python

https://geemap.org

A Python package for interactive geospaital analysis and visualization with Google Earth Engine.

giswqs

2024-01-14

2020-03-08

203

14.998595

https://avatars.githubusercontent.com/u/26841718?v=4

A Python package for interactive geospaital analysis and visualization with Google Earth Engine.

['colab', 'data-science', 'dataviz', 'earth-engine', 'earthengine', 'folium', 'geospatial', 'gis', 'google-earth-engine', 'image-processing', 'ipyleaflet', 'ipywidgets', 'jupyter', 'jupyter-notebook', 'landsat', 'mapping', 'remote-sensing', 'streamlit', 'streamlit-webapp']

2024-01-12

[('opengeos/leafmap', 0.7121515274047852, 'gis', 11), ('scitools/iris', 0.6783716082572937, 'gis', 0), ('residentmario/geoplot', 0.6778126358985901, 'gis', 0), ('raphaelquast/eomaps', 0.6554696559906006, 'gis', 3), ('holoviz/holoviz', 0.6438645124435425, 'viz', 0), ('bokeh/bokeh', 0.6420087218284607, 'viz', 1), ('holoviz/panel', 0.6401718258857727, 'viz', 2), ('gregorhd/mapcompare', 0.6100561022758484, 'gis', 0), ('visgl/deck.gl', 0.6095970869064331, 'viz', 0), ('plotly/dash', 0.6076993346214294, 'viz', 2), ('plotly/plotly.py', 0.5846720933914185, 'viz', 1), ('holoviz/geoviews', 0.5793654918670654, 'gis', 0), ('altair-viz/altair', 0.5686102509498596, 'viz', 0), ('geopandas/geopandas', 0.5684166550636292, 'gis', 2), ('sentinel-hub/eo-learn', 0.5640432834625244, 'gis', 0), ('maartenbreddels/ipyvolume', 0.5499334931373596, 'jupyter', 3), ('google/earthengine-api', 0.5498977899551392, 'gis', 0), ('osgeo/grass', 0.5491253137588501, 'gis', 6), ('earthlab/earthpy', 0.5480675101280212, 'gis', 0), ('vispy/vispy', 0.5475439429283142, 'viz', 0), ('python-visualization/folium', 0.5445337295532227, 'gis', 1), ('man-group/dtale', 0.5396121144294739, 'viz', 2), ('googleapis/google-api-python-client', 0.5369963645935059, 'util', 0), ('gradio-app/gradio', 0.534578800201416, 'viz', 1), ('kanaries/pygwalker', 0.5327471494674683, 'pandas', 0), ('has2k1/plotnine', 0.5272516012191772, 'viz', 0), ('vizzuhq/ipyvizzu', 0.5243290066719055, 'jupyter', 3), ('polyaxon/datatile', 0.5178652405738831, 'pandas', 1), ('imageio/imageio', 0.505904495716095, 'util', 0), ('radiantearth/radiant-mlhub', 0.5028256773948669, 'gis', 0), ('pytroll/satpy', 0.5017055869102478, 'gis', 0), ('mwaskom/seaborn', 0.5008442401885986, 'viz', 1)]

52

5

null

5.27

83

79

47

0

45

46

45

83

168

90

2

56

549

ml-dl

https://github.com/pytorch/botorch

[]

null

[]

null

pytorch/botorch

botorch

2,871

359

53

Jupyter Notebook

https://botorch.org/

Bayesian optimization in PyTorch

pytorch

2024-01-14

2018-07-30

287

9.998507

https://avatars.githubusercontent.com/u/21003710?v=4

Bayesian optimization in PyTorch

[]

2024-01-12

[('pyro-ppl/pyro', 0.6212801933288574, 'ml-dl', 0), ('intellabs/bayesian-torch', 0.6108170747756958, 'ml', 0), ('bayesianmodelingandcomputationinpython/bookcode_edition1', 0.5796522498130798, 'study', 0), ('pytorch/ignite', 0.5717622637748718, 'ml-dl', 0), ('nvidia/apex', 0.5640817880630493, 'ml-dl', 0), ('laekov/fastmoe', 0.5626605749130249, 'ml', 0), ('deepmind/kfac-jax', 0.55311119556427, 'math', 0), ('scikit-optimize/scikit-optimize', 0.5391286611557007, 'ml', 0), ('davidmrau/mixture-of-experts', 0.5366146564483643, 'ml', 0), ('pymc-devs/pymc3', 0.5349946618080139, 'ml', 0), ('tanelp/tiny-diffusion', 0.5327487587928772, 'diffusion', 0), ('mrdbourke/pytorch-deep-learning', 0.5209388136863708, 'study', 0), ('pytorch/captum', 0.509192168712616, 'ml-interpretability', 0), ('kshitij12345/torchnnprofiler', 0.5020992159843445, 'profiling', 0), ('skorch-dev/skorch', 0.5020517110824585, 'ml-dl', 0)]

108

4

null

6.67

131

111

66

0

10

8

10

131

512

90

3.9

56

436

gis

https://github.com/opengeos/leafmap

[]

null

[]

null

opengeos/leafmap

leafmap

2,809

326

52

Python

https://leafmap.org

A Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment

opengeos

2024-01-13

2021-03-10

150

18.620265

https://avatars.githubusercontent.com/u/129896036?v=4

A Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment

['data-science', 'dataviz', 'folium', 'geoparquet', 'geopython', 'geospatial', 'geospatial-analysis', 'gis', 'ipyleaflet', 'jupyter', 'jupyter-notebook', 'leafmap', 'mapping', 'plotly', 'streamlit', 'streamlit-webapp', 'whiteboxtools']

2024-01-11

[('giswqs/geemap', 0.7121515274047852, 'gis', 11), ('residentmario/geoplot', 0.6929628252983093, 'gis', 0), ('raphaelquast/eomaps', 0.6778762936592102, 'gis', 3), ('geopandas/geopandas', 0.671466052532196, 'gis', 3), ('vizzuhq/ipyvizzu', 0.6331526637077332, 'jupyter', 3), ('holoviz/panel', 0.6154477596282959, 'viz', 3), ('artelys/geonetworkx', 0.6138547658920288, 'gis', 0), ('holoviz/geoviews', 0.6069517135620117, 'gis', 0), ('holoviz/holoviz', 0.6019681692123413, 'viz', 0), ('gregorhd/mapcompare', 0.6006041169166565, 'gis', 0), ('plotly/plotly.py', 0.5990200638771057, 'viz', 2), ('bokeh/bokeh', 0.5971899032592773, 'viz', 1), ('giswqs/mapwidget', 0.5904461741447449, 'gis', 4), ('wesm/pydata-book', 0.5878331065177917, 'study', 0), ('scitools/iris', 0.5820508003234863, 'gis', 0), ('ipython/ipyparallel', 0.580319344997406, 'perf', 1), ('quantopian/qgrid', 0.5799870491027832, 'jupyter', 0), ('maartenbreddels/ipyvolume', 0.5771999359130859, 'jupyter', 3), ('geopandas/contextily', 0.5741623044013977, 'gis', 1), ('earthlab/earthpy', 0.572256863117218, 'gis', 0), ('jakevdp/pythondatasciencehandbook', 0.5667238235473633, 'study', 1), ('pysal/pysal', 0.5648621320724487, 'gis', 0), ('darribas/gds_env', 0.563289999961853, 'gis', 0), ('plotly/dash', 0.5570528507232666, 'viz', 3), ('scitools/cartopy', 0.5553449988365173, 'gis', 0), ('has2k1/plotnine', 0.5541620254516602, 'viz', 0), ('man-group/dtale', 0.5516546368598938, 'viz', 2), ('fchollet/deep-learning-with-python-notebooks', 0.5463659763336182, 'study', 0), ('cohere-ai/notebooks', 0.546214759349823, 'llm', 0), ('altair-viz/altair', 0.5457186698913574, 'viz', 0), ('marceloprates/prettymaps', 0.5452340841293335, 'viz', 1), ('pyston/pyston', 0.5413333773612976, 'util', 0), ('toblerity/rtree', 0.5405087471008301, 'gis', 0), ('pypy/pypy', 0.5401880741119385, 'util', 0), ('python-visualization/folium', 0.5398542284965515, 'gis', 1), ('aws/graph-notebook', 0.5389112830162048, 'jupyter', 2), ('jupyter-widgets/ipyleaflet', 0.5388780832290649, 'gis', 1), ('kanaries/pygwalker', 0.5377007722854614, 'pandas', 1), ('pyproj4/pyproj', 0.5364670157432556, 'gis', 1), ('pytoolz/toolz', 0.5356908440589905, 'util', 0), ('python/cpython', 0.5353587865829468, 'util', 0), ('jupyter-lsp/jupyterlab-lsp', 0.5345747470855713, 'jupyter', 2), ('makepath/xarray-spatial', 0.5318371057510376, 'gis', 0), ('openeventdata/mordecai', 0.5265222191810608, 'gis', 0), ('eleutherai/pyfra', 0.525818407535553, 'ml', 0), ('jalammar/ecco', 0.5254456996917725, 'ml-interpretability', 0), ('voila-dashboards/voila', 0.5204005241394043, 'jupyter', 2), ('pandas-dev/pandas', 0.5185487866401672, 'pandas', 1), ('pyglet/pyglet', 0.5158253312110901, 'gamedev', 0), ('osgeo/grass', 0.5151031017303467, 'gis', 5), ('uber/h3-py', 0.5105132460594177, 'gis', 2), ('cloudsen12/easystac', 0.5067197680473328, 'gis', 1), ('bitcraft/pytmx', 0.5061635375022888, 'gamedev', 0), ('scikit-mobility/scikit-mobility', 0.5058870911598206, 'gis', 1), ('amaargiru/pyroad', 0.503073513507843, 'study', 0)]

29

6

null

5.35

77

74

35

0

58

43

58

77

104

90

1.4

56

806

data

https://github.com/datafold/data-diff

[]

null

[]

null

datafold/data-diff

data-diff

2,686

189

21

Python

https://docs.datafold.com

Compare tables within or across databases

datafold

2024-01-14

2022-03-07

99

27.092219

https://avatars.githubusercontent.com/u/63129412?v=4

Compare tables within or across databases

['data', 'data-diffing', 'data-engineering', 'data-quality', 'data-quality-monitoring', 'data-science', 'database', 'databricks-sql', 'dataengineering', 'dataquality', 'dbt', 'mysql', 'oracle-database', 'postgres', 'postgresql', 'rdbms', 'snowflake', 'sql', 'trino']

2024-01-12

[('ibis-project/ibis', 0.5967792272567749, 'data', 6), ('tobymao/sqlglot', 0.5574495196342468, 'data', 5), ('tiangolo/sqlmodel', 0.5563005805015564, 'data', 1), ('dbt-labs/dbt-core', 0.550411581993103, 'ml-ops', 0), ('great-expectations/great_expectations', 0.5429127216339111, 'ml-ops', 4), ('unionai-oss/pandera', 0.5363107919692993, 'pandas', 0)]

53

2

null

11.88

133

98

23

0

48

32

48

133

120

90

0.9

56

1,628

llm

https://github.com/next-gpt/next-gpt

[]

null

[]

null

next-gpt/next-gpt

NExT-GPT

2,579

266

57

Python

https://next-gpt.github.io/

Code and models for NExT-GPT: Any-to-Any Multimodal Large Language Model

next-gpt

2024-01-13

2023-08-30

21

117.993464

null

Code and models for NExT-GPT: Any-to-Any Multimodal Large Language Model

['chatgpt', 'foundation-models', 'gpt-4', 'instruction-tuning', 'large-language-models', 'llm', 'multi-modal-chatgpt', 'multimodal', 'visual-language-learning']

2024-01-09

[('microsoft/autogen', 0.7022780776023865, 'llm', 2), ('hannibal046/awesome-llm', 0.6860809922218323, 'study', 0), ('lianjiatech/belle', 0.6763371229171753, 'llm', 0), ('mlc-ai/web-llm', 0.6524577140808105, 'llm', 2), ('xtekky/gpt4free', 0.6495850086212158, 'llm', 2), ('guidance-ai/guidance', 0.6470729112625122, 'llm', 1), ('hiyouga/llama-factory', 0.6337036490440369, 'llm', 3), ('hiyouga/llama-efficient-tuning', 0.6337035894393921, 'llm', 3), ('thudm/chatglm2-6b', 0.6282567381858826, 'llm', 2), ('lm-sys/fastchat', 0.6228191256523132, 'llm', 0), ('openlmlab/moss', 0.6183462738990784, 'llm', 2), ('microsoft/lora', 0.6170973181724548, 'llm', 0), ('haotian-liu/llava', 0.6144143342971802, 'llm', 6), ('bobazooba/xllm', 0.61397784948349, 'llm', 4), ('baichuan-inc/baichuan-13b', 0.6081295013427734, 'llm', 3), ('lupantech/chameleon-llm', 0.6010711193084717, 'llm', 3), ('docarray/docarray', 0.5986325144767761, 'data', 1), ('optimalscale/lmflow', 0.5973320603370667, 'llm', 1), ('ctlllll/llm-toolmaker', 0.5953162908554077, 'llm', 0), ('freedomintelligence/llmzoo', 0.5918599963188171, 'llm', 0), ('ai21labs/lm-evaluation', 0.5911809802055359, 'llm', 0), ('li-plus/chatglm.cpp', 0.5851370096206665, 'llm', 1), ('microsoft/torchscale', 0.582415759563446, 'llm', 1), ('sjtu-ipads/powerinfer', 0.5799466967582703, 'llm', 2), ('blinkdl/chatrwkv', 0.5798339247703552, 'llm', 1), ('fasteval/fasteval', 0.57789546251297, 'llm', 1), ('young-geng/easylm', 0.5767945647239685, 'llm', 1), ('nomic-ai/gpt4all', 0.5750716328620911, 'llm', 0), ('nvlabs/prismer', 0.5736103057861328, 'diffusion', 0), ('eth-sri/lmql', 0.5689839124679565, 'llm', 1), ('oobabooga/text-generation-webui', 0.5688201785087585, 'llm', 0), ('bigscience-workshop/megatron-deepspeed', 0.5671409964561462, 'llm', 0), ('microsoft/megatron-deepspeed', 0.5671409964561462, 'llm', 0), ('salesforce/xgen', 0.5664035081863403, 'llm', 2), ('cg123/mergekit', 0.5641329884529114, 'llm', 1), ('lightning-ai/lit-llama', 0.5547515153884888, 'llm', 0), ('mnotgod96/appagent', 0.5528967976570129, 'llm', 2), ('run-llama/rags', 0.5521267652511597, 'llm', 2), ('huggingface/text-generation-inference', 0.5511967539787292, 'llm', 0), ('togethercomputer/redpajama-data', 0.5498401522636414, 'llm', 0), ('salesforce/blip', 0.5469942092895508, 'diffusion', 0), ('infinitylogesh/mutate', 0.5463948845863342, 'nlp', 0), ('juncongmoo/pyllama', 0.5461319088935852, 'llm', 0), ('killianlucas/open-interpreter', 0.5455114841461182, 'llm', 2), ('intel/intel-extension-for-transformers', 0.5425037145614624, 'perf', 0), ('dylanhogg/llmgraph', 0.5404556393623352, 'ml', 2), ('bigscience-workshop/petals', 0.5393829941749573, 'data', 1), ('confident-ai/deepeval', 0.5388375520706177, 'testing', 2), ('ofa-sys/ofa', 0.538471519947052, 'llm', 1), ('hwchase17/langchain', 0.5355835556983948, 'llm', 0), ('nvidia/tensorrt-llm', 0.5343412160873413, 'viz', 0), ('facebookresearch/seamless_communication', 0.5332794785499573, 'nlp', 0), ('guardrails-ai/guardrails', 0.5325504541397095, 'llm', 1), ('reasoning-machines/pal', 0.532139778137207, 'llm', 1), ('yueyu1030/attrprompt', 0.5283357501029968, 'llm', 1), ('salesforce/codet5', 0.5271520614624023, 'nlp', 1), ('microsoft/unilm', 0.5269091129302979, 'nlp', 3), ('embedchain/embedchain', 0.5254507064819336, 'llm', 2), ('keirp/automatic_prompt_engineer', 0.525351881980896, 'llm', 0), ('openai/gpt-2', 0.5251544713973999, 'llm', 0), ('cstankonrad/long_llama', 0.5235233306884766, 'llm', 0), ('zhudotexe/kani', 0.5206196904182434, 'llm', 3), ('databrickslabs/dolly', 0.5201497077941895, 'llm', 0), ('mooler0410/llmspracticalguide', 0.5197857022285461, 'study', 1), ('whu-zqh/chatgpt-vs.-bert', 0.515221357345581, 'llm', 1), ('salesforce/codegen', 0.5129567384719849, 'nlp', 1), ('ray-project/ray-llm', 0.5125154256820679, 'llm', 2), ('lucidrains/toolformer-pytorch', 0.5125038027763367, 'llm', 0), ('ludwig-ai/ludwig', 0.5110254287719727, 'ml-ops', 1), ('explosion/spacy-llm', 0.5109996199607849, 'llm', 3), ('eleutherai/gpt-neo', 0.5107851624488831, 'llm', 0), ('langchain-ai/langgraph', 0.5100759863853455, 'llm', 0), ('minedojo/voyager', 0.509900689125061, 'llm', 1), ('huawei-noah/pretrained-language-model', 0.5096499919891357, 'nlp', 0), ('srush/minichain', 0.5092249512672424, 'llm', 0), ('h2oai/h2o-llmstudio', 0.5090202689170837, 'llm', 2), ('conceptofmind/toolformer', 0.5089335441589355, 'llm', 0), ('lingjzhu/charsiug2p', 0.5078827738761902, 'nlp', 0), ('epfllm/meditron', 0.5075371265411377, 'llm', 0), ('deepset-ai/haystack', 0.5068576335906982, 'llm', 2), ('eleutherai/lm-evaluation-harness', 0.5040009617805481, 'llm', 0), ('agenta-ai/agenta', 0.503362774848938, 'llm', 2), ('microsoft/generative-ai-for-beginners', 0.5027459859848022, 'study', 1), ('moymix/taskmatrix', 0.5018583536148071, 'llm', 1), ('openbmb/toolbench', 0.5017238259315491, 'llm', 1), ('luodian/otter', 0.501610517501831, 'llm', 5), ('thilinarajapakse/simpletransformers', 0.5003290772438049, 'nlp', 0)]

4

2

null

4.06

58

21

5

0

58

30

90

0.5

56

835

ml

https://github.com/aws/sagemaker-python-sdk

[]

null

[]

null

aws/sagemaker-python-sdk

sagemaker-python-sdk

1,995

1,104

132

Python

https://sagemaker.readthedocs.io/

A library for training and deploying machine learning models on Amazon SageMaker

aws

2024-01-12

2017-11-14

324

6.157407

https://avatars.githubusercontent.com/u/2232217?v=4

A library for training and deploying machine learning models on Amazon SageMaker

['aws', 'huggingface', 'machine-learning', 'mxnet', 'pytorch', 'sagemaker', 'tensorflow']

2024-01-11

[('aws-samples/sagemaker-ssh-helper', 0.671806812286377, 'util', 3), ('huggingface/huggingface_hub', 0.6623826026916504, 'ml', 2), ('mlflow/mlflow', 0.6176590919494629, 'ml-ops', 1), ('ashleve/lightning-hydra-template', 0.6082078814506531, 'util', 1), ('kubeflow/fairing', 0.5987374186515808, 'ml-ops', 0), ('merantix-momentum/squirrel-core', 0.5961750149726868, 'ml', 3), ('horovod/horovod', 0.5958705544471741, 'ml-ops', 4), ('determined-ai/determined', 0.5937497019767761, 'ml-ops', 3), ('rasbt/machine-learning-book', 0.586579442024231, 'study', 2), ('huggingface/exporters', 0.5837609171867371, 'ml', 3), ('huggingface/datasets', 0.5822443962097168, 'nlp', 3), ('tensorflow/tensorflow', 0.578117311000824, 'ml-dl', 2), ('skorch-dev/skorch', 0.5779036283493042, 'ml-dl', 3), ('uber/petastorm', 0.5683594346046448, 'data', 3), ('huggingface/transformers', 0.5665184855461121, 'nlp', 3), ('pytorch/ignite', 0.5633373856544495, 'ml-dl', 2), ('tensorlayer/tensorlayer', 0.5589292645454407, 'ml-rl', 1), ('gradio-app/gradio', 0.5586919188499451, 'viz', 1), ('ggerganov/ggml', 0.5583137273788452, 'ml', 1), ('titanml/takeoff', 0.5581379532814026, 'llm', 0), ('intel/intel-extension-for-pytorch', 0.5577678680419922, 'perf', 2), ('microsoft/nni', 0.5550652146339417, 'ml', 3), ('google/tf-quant-finance', 0.5465176105499268, 'finance', 1), ('radiantearth/radiant-mlhub', 0.5445782542228699, 'gis', 1), ('ml-tooling/opyrator', 0.5434074401855469, 'viz', 1), ('firmai/industry-machine-learning', 0.5424572229385376, 'study', 1), ('wandb/client', 0.5404186248779297, 'ml', 3), ('polyaxon/polyaxon', 0.5382318496704102, 'ml-ops', 4), ('ageron/handson-ml2', 0.5365365743637085, 'ml', 0), ('karpathy/micrograd', 0.5261572003364563, 'study', 0), ('keras-team/autokeras', 0.5244501233100891, 'ml-dl', 2), ('eventual-inc/daft', 0.5235341787338257, 'pandas', 1), ('pytorch/rl', 0.5228525996208191, 'ml-rl', 2), ('activeloopai/deeplake', 0.5221602320671082, 'ml-ops', 3), ('tlkh/tf-metal-experiments', 0.5217053890228271, 'perf', 1), ('microsoft/flaml', 0.5215294361114502, 'ml', 1), ('oml-team/open-metric-learning', 0.5199127197265625, 'ml', 1), ('dylanhogg/awesome-python', 0.5184698104858398, 'study', 1), ('nvidia/deeplearningexamples', 0.5177861452102661, 'ml-dl', 3), ('tensorflow/tensor2tensor', 0.5145456790924072, 'ml', 1), ('microsoft/onnxruntime', 0.513953447341919, 'ml', 3), ('rafiqhasan/auto-tensorflow', 0.512946367263794, 'ml-dl', 2), ('googlecloudplatform/vertex-ai-samples', 0.5073953866958618, 'ml', 0), ('pycaret/pycaret', 0.5068821310997009, 'ml', 1), ('adap/flower', 0.506871223449707, 'ml-ops', 3), ('ray-project/ray', 0.5026758909225464, 'ml-ops', 3), ('lightly-ai/lightly', 0.5022170543670654, 'ml', 2), ('dmlc/xgboost', 0.5017920732498169, 'ml', 1)]

417

2

null

12.08

465

368

75

0

88

91

88

465

2,810

90

6

56

1,242

ml-interpretability

https://github.com/arize-ai/phoenix

[]

null

[]

null

arize-ai/phoenix

phoenix

1,906

128

23

Jupyter Notebook

https://docs.arize.com/phoenix

AI Observability & Evaluation - Evaluate, troubleshoot, and fine tune your LLM, CV, and NLP models in a notebook.

arize-ai

2024-01-13

2022-11-09

63

29.847875

https://avatars.githubusercontent.com/u/59858760?v=4

AI Observability & Evaluation - Evaluate, troubleshoot, and fine tune your LLM, CV, and NLP models in a notebook.

['ai-monitoring', 'ai-observability', 'ai-roi', 'clustering', 'llm-eval', 'llmops', 'ml-monitoring', 'ml-observability', 'mlops', 'model-monitoring', 'model-observability', 'umap']

2024-01-12

[('giskard-ai/giskard', 0.6145030856132507, 'data', 2), ('microsoft/lmops', 0.5890821814537048, 'llm', 0), ('llmware-ai/llmware', 0.5607779026031494, 'llm', 0), ('bentoml/bentoml', 0.547683835029602, 'ml-ops', 2), ('microsoft/promptflow', 0.5460477471351624, 'llm', 0), ('tigerlab-ai/tiger', 0.5459373593330383, 'llm', 0), ('confident-ai/deepeval', 0.5458160042762756, 'testing', 1), ('truera/trulens', 0.532617449760437, 'llm', 1), ('interpretml/interpret', 0.5245933532714844, 'ml-interpretability', 0), ('lastmile-ai/aiconfig', 0.5230908393859863, 'util', 0), ('mlc-ai/mlc-llm', 0.5153992772102356, 'llm', 0), ('nebuly-ai/nebullvm', 0.5097155570983887, 'perf', 0), ('googlecloudplatform/vertex-ai-samples', 0.5083956122398376, 'ml', 1), ('cheshire-cat-ai/core', 0.5057440400123596, 'llm', 0), ('csinva/imodels', 0.5046104192733765, 'ml', 0), ('evidentlyai/evidently', 0.5009012818336487, 'ml-ops', 2), ('openai/evals', 0.500573456287384, 'llm', 0)]

30

1

null

26.98

518

437

14

0

75

90

75

519

394

90

0.8

56

1,743

llm

https://github.com/microsoft/llmlingua

['inference', 'performance']

null

[]

null

microsoft/llmlingua

LLMLingua

1,887

93

17

Python

https://llmlingua.com/

To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.

microsoft

2024-01-14

2023-07-07

29

63.811594

https://avatars.githubusercontent.com/u/6154722?v=4

To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.

[]

['inference', 'performance']

2024-01-13

[('vllm-project/vllm', 0.6239213347434998, 'llm', 1), ('intel/intel-extension-for-transformers', 0.6135388016700745, 'perf', 0), ('lightning-ai/lit-gpt', 0.5566024780273438, 'llm', 0), ('bentoml/openllm', 0.5037171244621277, 'ml-ops', 0)]

7

3

null

0.67

49

26

6

0

4

8

4

49

70

90

1.4

56

463

ml-dl

https://github.com/pytorch/torchrec

[]

null

[]

null

pytorch/torchrec

torchrec

1,625

328

29

Python

null

Pytorch domain library for recommendation systems

pytorch

2024-01-14

2021-07-12

133

12.204936

https://avatars.githubusercontent.com/u/21003710?v=4

Pytorch domain library for recommendation systems

['cuda', 'deep-learning', 'gpu', 'pytorch', 'recommendation-system', 'recommender-system', 'sharding']

2024-01-13

[('rucaibox/recbole', 0.7371825575828552, 'ml', 3), ('nicolashug/surprise', 0.5874725580215454, 'ml', 0), ('pytorch/data', 0.5872920751571655, 'data', 0), ('pytorch/ignite', 0.5860687494277954, 'ml-dl', 2), ('pyg-team/pytorch_geometric', 0.570334255695343, 'ml-dl', 2), ('cvxgrp/pymde', 0.5692107677459717, 'ml', 3), ('blackhc/toma', 0.5616428256034851, 'ml-dl', 2), ('microsoft/recommenders', 0.5602710247039795, 'study', 2), ('mrdbourke/pytorch-deep-learning', 0.5445482730865479, 'study', 2), ('rasbt/machine-learning-book', 0.5437749624252319, 'study', 2), ('oml-team/open-metric-learning', 0.5388403534889221, 'ml', 2), ('cupy/cupy', 0.5291244387626648, 'math', 2), ('intel/intel-extension-for-pytorch', 0.5260089635848999, 'perf', 2), ('google/tf-quant-finance', 0.5250528454780579, 'finance', 1), ('skorch-dev/skorch', 0.5207085609436035, 'ml-dl', 1), ('a-r-j/graphein', 0.5193598866462708, 'sim', 2), ('rentruewang/koila', 0.5190505385398865, 'ml', 2), ('xl0/lovely-tensors', 0.5139912366867065, 'ml-dl', 2), ('uber/petastorm', 0.5117344260215759, 'data', 2), ('qdrant/fastembed', 0.5069307088851929, 'ml', 0), ('catboost/catboost', 0.5050163269042969, 'ml', 2), ('facebookresearch/pytorch3d', 0.5049778819084167, 'ml-dl', 0), ('kevinmusgrave/pytorch-metric-learning', 0.5045345425605774, 'ml', 2), ('rapidsai/cudf', 0.5002225637435913, 'pandas', 2)]

198

5

null

9.6

194

142

30

0

5

4

5

194

572

90

2.9

56

1,541

llm

https://github.com/weaviate/verba

['retrieval-augmentation']

null

[]

null

weaviate/verba

Verba

1,585

157

31

Python

null

Retrieval Augmented Generation (RAG) chatbot powered by Weaviate

weaviate

2024-01-14

2023-07-28

26

59.650538

https://avatars.githubusercontent.com/u/37794290?v=4

Retrieval Augmented Generation (RAG) chatbot powered by Weaviate

[]

['retrieval-augmentation']

2024-01-02

[('rcgai/simplyretrieve', 0.6520878076553345, 'llm', 0), ('embedchain/embedchain', 0.5736026167869568, 'llm', 0), ('microsoft/chatgpt-robot-manipulation-prompts', 0.5466259121894836, 'llm', 0), ('lm-sys/fastchat', 0.5395397543907166, 'llm', 0), ('openlmlab/moss', 0.5387402772903442, 'llm', 0), ('langchain-ai/chat-langchain', 0.5274889469146729, 'llm', 0), ('togethercomputer/openchatkit', 0.5258392691612244, 'nlp', 0), ('cheshire-cat-ai/core', 0.5184066295623779, 'llm', 0)]

8

1

null

2.92

91

51

6

0

3

6

3

91

196

90

2.2

56

290

ml-ops

https://github.com/dagworks-inc/hamilton

['mlops']

null

[]

null

dagworks-inc/hamilton

hamilton

1,120

63

12

Jupyter Notebook

https://hamilton.dagworks.io/en/latest/

Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.

dagworks-inc

2024-01-13

2023-02-23

48

22.991202

https://avatars.githubusercontent.com/u/116846391?v=4

Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.

['dag', 'data-analysis', 'data-engineering', 'data-science', 'dataframe', 'etl', 'etl-framework', 'etl-pipeline', 'feature-engineering', 'featurization', 'lineage', 'llmops', 'machine-learning', 'mlops', 'numpy', 'orchestration', 'pandas', 'software-engineering']

2024-01-13

[('python-odin/odin', 0.6443514227867126, 'util', 0), ('polyaxon/datatile', 0.6286333203315735, 'pandas', 3), ('orchest/orchest', 0.6139141917228699, 'ml-ops', 5), ('mage-ai/mage-ai', 0.6080176830291748, 'ml-ops', 5), ('ploomber/ploomber', 0.6052381992340088, 'ml-ops', 4), ('fastai/fastcore', 0.603600263595581, 'util', 0), ('krzjoa/awesome-python-data-science', 0.5971183776855469, 'study', 3), ('airbytehq/airbyte', 0.5934673547744751, 'data', 3), ('dagster-io/dagster', 0.5917893052101135, 'ml-ops', 5), ('merantix-momentum/squirrel-core', 0.5907508730888367, 'ml', 2), ('fugue-project/fugue', 0.5906447768211365, 'pandas', 2), ('pandas-dev/pandas', 0.590579092502594, 'pandas', 4), ('plotly/dash', 0.5894344449043274, 'viz', 1), ('backtick-se/cowait', 0.5880764722824097, 'util', 2), ('avaiga/taipy', 0.5867727994918823, 'data', 3), ('meltano/meltano', 0.5787143111228943, 'ml-ops', 1), ('wandb/client', 0.5770619511604309, 'ml', 3), ('hi-primus/optimus', 0.5767509341239929, 'ml-ops', 3), ('kestra-io/kestra', 0.5751848816871643, 'ml-ops', 3), ('eventual-inc/daft', 0.5710514783859253, 'pandas', 4), ('gradio-app/gradio', 0.5623276233673096, 'viz', 3), ('dylanhogg/awesome-python', 0.5567782521247864, 'study', 3), ('eleutherai/pyfra', 0.5552157163619995, 'ml', 0), ('polyaxon/polyaxon', 0.5525692701339722, 'ml-ops', 3), ('flyteorg/flyte', 0.549081027507782, 'ml-ops', 4), ('kubeflow-kale/kale', 0.5480688214302063, 'ml-ops', 1), ('ydataai/ydata-profiling', 0.5421671867370605, 'pandas', 4), ('featurelabs/featuretools', 0.5415907502174377, 'ml', 3), ('unionai-oss/pandera', 0.5392426252365112, 'pandas', 1), ('goldmansachs/gs-quant', 0.5357715487480164, 'finance', 0), ('huggingface/datasets', 0.5354235172271729, 'nlp', 3), ('google/pyglove', 0.5348206162452698, 'util', 1), ('thealgorithms/python', 0.5340306162834167, 'study', 0), ('pytoolz/toolz', 0.5323624014854431, 'util', 0), ('malloydata/malloy-py', 0.532253086566925, 'data', 0), ('pathwaycom/pathway', 0.5315225720405579, 'data', 1), ('rasbt/mlxtend', 0.5286049842834473, 'ml', 2), ('google/ml-metadata', 0.5270819664001465, 'ml-ops', 0), ('ranaroussi/quantstats', 0.5268656015396118, 'finance', 0), ('kubeflow/fairing', 0.5266019105911255, 'ml-ops', 0), ('man-group/dtale', 0.525833010673523, 'viz', 3), ('selfexplainml/piml-toolbox', 0.5237611532211304, 'ml-interpretability', 0), ('firmai/industry-machine-learning', 0.5236888527870178, 'study', 2), ('thoth-station/micropipenv', 0.522192656993866, 'util', 0), ('netflix/metaflow', 0.519896924495697, 'ml-ops', 3), ('epistasislab/tpot', 0.5198063850402832, 'ml', 3), ('holoviz/panel', 0.5194111466407776, 'viz', 0), ('great-expectations/great_expectations', 0.5179693102836609, 'ml-ops', 3), ('spotify/luigi', 0.5168716907501221, 'ml-ops', 0), ('scikit-mobility/scikit-mobility', 0.5164218544960022, 'gis', 2), ('tobymao/sqlglot', 0.5160204768180847, 'data', 0), ('scikit-learn/scikit-learn', 0.514525830745697, 'ml', 3), ('mlflow/mlflow', 0.5135458111763, 'ml-ops', 1), ('lk-geimfari/mimesis', 0.5131853222846985, 'data', 2), ('whylabs/whylogs', 0.5131041407585144, 'util', 3), ('keon/algorithms', 0.5108981728553772, 'util', 0), ('pythagora-io/gpt-pilot', 0.510085940361023, 'llm', 0), ('apache/airflow', 0.5085076093673706, 'ml-ops', 7), ('googlecloudplatform/vertex-ai-samples', 0.5069316625595093, 'ml', 2), ('ibis-project/ibis', 0.5063190460205078, 'data', 1), ('pypa/pipenv', 0.5052401423454285, 'util', 0), ('linealabs/lineapy', 0.5050464868545532, 'jupyter', 0), ('dlt-hub/dlt', 0.5049058198928833, 'data', 1), ('saulpw/visidata', 0.5007401704788208, 'term', 1)]

40

3

null

12.56

185

148

11

0

55

84

55

186

240

90

1.3

56

1,875

llm

https://github.com/agenta-ai/agenta

['llmops']

null

[]

null

agenta-ai/agenta

agenta

623

126

13

Python

http://www.agenta.ai

The all-in-one LLMOps platform: prompt management, evaluation, human feedback, and deployment all in one place.

agenta-ai

2024-01-14

2023-04-26

39

15.630824

https://avatars.githubusercontent.com/u/127993667?v=4

The all-in-one LLMOps platform: prompt management, evaluation, human feedback, and deployment all in one place.

['langchain', 'large-language-models', 'llama-index', 'llm', 'llm-evaluation', 'llm-framework', 'llm-tools', 'llmops', 'llms', 'prompt-engineering', 'prompt-management', 'prompt-toolkit', 'rag', 'rag-evaluation']

2024-01-12

[('confident-ai/deepeval', 0.690017819404602, 'testing', 3), ('hegelai/prompttools', 0.6764405965805054, 'llm', 3), ('eugeneyan/open-llms', 0.6486678719520569, 'study', 3), ('hwchase17/langchain', 0.6438751816749573, 'llm', 1), ('alpha-vllm/llama2-accessory', 0.6384699940681458, 'llm', 0), ('bentoml/openllm', 0.6264759302139282, 'ml-ops', 2), ('argilla-io/argilla', 0.6207625269889832, 'nlp', 2), ('microsoft/promptflow', 0.6172305941581726, 'llm', 2), ('citadel-ai/langcheck', 0.613926351070404, 'llm', 0), ('young-geng/easylm', 0.6034758687019348, 'llm', 1), ('h2oai/h2o-llmstudio', 0.6011561751365662, 'llm', 1), ('promptslab/promptify', 0.5992403030395508, 'nlp', 3), ('deepset-ai/haystack', 0.5929967761039734, 'llm', 1), ('keirp/automatic_prompt_engineer', 0.5762568116188049, 'llm', 1), ('guidance-ai/guidance', 0.5751789808273315, 'llm', 1), ('nomic-ai/gpt4all', 0.5681662559509277, 'llm', 0), ('salesforce/xgen', 0.5658103227615356, 'llm', 2), ('hiyouga/llama-factory', 0.5645887851715088, 'llm', 3), ('hiyouga/llama-efficient-tuning', 0.5645886659622192, 'llm', 3), ('pathwaycom/llm-app', 0.5643110275268555, 'llm', 3), ('tigerlab-ai/tiger', 0.5620597004890442, 'llm', 3), ('bigscience-workshop/petals', 0.5601279735565186, 'data', 1), ('lm-sys/fastchat', 0.5597670674324036, 'llm', 0), ('deep-diver/pingpong', 0.557935893535614, 'llm', 0), ('microsoft/lmops', 0.5574962496757507, 'llm', 1), ('microsoft/autogen', 0.557157039642334, 'llm', 2), ('openai/evals', 0.5553388595581055, 'llm', 0), ('mooler0410/llmspracticalguide', 0.5545148849487305, 'study', 1), ('neulab/prompt2model', 0.5488535761833191, 'llm', 0), ('nat/openplayground', 0.5450541973114014, 'llm', 0), ('salesforce/codet5', 0.5426530241966248, 'nlp', 1), ('intel/intel-extension-for-transformers', 0.5398895144462585, 'perf', 0), ('night-chen/toolqa', 0.539746880531311, 'llm', 1), ('run-llama/llama-lab', 0.5381309986114502, 'llm', 1), ('conceptofmind/toolformer', 0.5377708673477173, 'llm', 0), ('promptslab/awesome-prompt-engineering', 0.53215092420578, 'study', 2), ('nebuly-ai/nebullvm', 0.5309828519821167, 'perf', 2), ('microsoft/promptcraft-robotics', 0.5304033756256104, 'sim', 2), ('langchain-ai/langsmith-cookbook', 0.5301238894462585, 'llm', 0), ('explosion/spacy-llm', 0.5294641256332397, 'llm', 3), ('lianjiatech/belle', 0.5287581086158752, 'llm', 0), ('microsoft/torchscale', 0.5262821912765503, 'llm', 0), ('bigscience-workshop/promptsource', 0.52383953332901, 'nlp', 0), ('openbmb/toolbench', 0.5236167907714844, 'llm', 0), ('ibm/dromedary', 0.5226309895515442, 'llm', 0), ('ai21labs/lm-evaluation', 0.5219810009002686, 'llm', 0), ('alphasecio/langchain-examples', 0.5152485370635986, 'llm', 2), ('langchain-ai/langgraph', 0.5138852000236511, 'llm', 1), ('epfllm/meditron', 0.5137256979942322, 'llm', 0), ('ray-project/ray-llm', 0.5125582218170166, 'llm', 3), ('ajndkr/lanarky', 0.5057575702667236, 'llm', 1), ('iryna-kondr/scikit-llm', 0.5052707195281982, 'llm', 1), ('next-gpt/next-gpt', 0.503362774848938, 'llm', 2), ('hazyresearch/ama_prompting', 0.5027536153793335, 'llm', 1), ('deep-diver/llm-as-chatbot', 0.5022589564323425, 'llm', 0)]

55

5

null

73.85

505

427

9

0

55

74

55

507

448

90

0.9

56

943

ml

https://github.com/lutzroeder/netron

[]

null

[]

null

lutzroeder/netron

netron

25,153

2,629

296

JavaScript

https://netron.app

Visualizer for neural network, deep learning and machine learning models

lutzroeder

2024-01-14

2010-12-26

683

36.811834

null

Visualizer for neural network, deep learning and machine learning models

['ai', 'caffe', 'caffe2', 'coreml', 'darknet', 'deep-learning', 'deeplearning', 'keras', 'machine-learning', 'machinelearning', 'ml', 'mxnet', 'neural-network', 'onnx', 'paddle', 'pytorch', 'tensorflow', 'tensorflow-lite', 'torch', 'visualizer']

2024-01-14

[('neuralmagic/sparseml', 0.6401857137680054, 'ml-dl', 4), ('roboflow/supervision', 0.6290085911750793, 'ml', 4), ('onnx/onnx', 0.616361141204834, 'ml', 9), ('mosaicml/composer', 0.6044427156448364, 'ml-dl', 4), ('rwightman/pytorch-image-models', 0.601951003074646, 'ml-dl', 1), ('ddbourgin/numpy-ml', 0.6000135540962219, 'ml', 1), ('huggingface/datasets', 0.5983027219772339, 'nlp', 4), ('polyaxon/polyaxon', 0.5946682095527649, 'ml-ops', 8), ('tensorflow/lucid', 0.5944969654083252, 'ml-interpretability', 2), ('activeloopai/deeplake', 0.5856375694274902, 'ml-ops', 6), ('nvidia/deeplearningexamples', 0.5856183767318726, 'ml-dl', 4), ('nyandwi/modernconvnets', 0.584083616733551, 'ml-dl', 2), ('neuralmagic/deepsparse', 0.5835353136062622, 'nlp', 2), ('pytorch/ignite', 0.5811353325843811, 'ml-dl', 4), ('huggingface/exporters', 0.5719174742698669, 'ml', 5), ('tensorflow/tensorflow', 0.571031391620636, 'ml-dl', 5), ('districtdatalabs/yellowbrick', 0.570451557636261, 'ml', 2), ('explosion/thinc', 0.5670014023780823, 'ml-dl', 6), ('microsoft/onnxruntime', 0.5668833255767822, 'ml', 5), ('aleju/imgaug', 0.5660139322280884, 'ml', 2), ('wandb/client', 0.5644053816795349, 'ml', 5), ('deci-ai/super-gradients', 0.5625087022781372, 'ml-dl', 3), ('bentoml/bentoml', 0.5586127042770386, 'ml-ops', 3), ('tensorflow/tensor2tensor', 0.5569348335266113, 'ml', 2), ('keras-team/keras', 0.5549449920654297, 'ml-dl', 4), ('man-group/dtale', 0.5549408793449402, 'viz', 0), ('determined-ai/determined', 0.5507928729057312, 'ml-ops', 5), ('open-mmlab/mmediting', 0.5503832101821899, 'ml', 2), ('xl0/lovely-tensors', 0.549081027507782, 'ml-dl', 2), ('christoschristofidis/awesome-deep-learning', 0.5479288101196289, 'study', 3), ('keras-team/autokeras', 0.5447315573692322, 'ml-dl', 4), ('pyg-team/pytorch_geometric', 0.5430858731269836, 'ml-dl', 2), ('towhee-io/towhee', 0.5428910851478577, 'ml-ops', 1), ('harisiqbal88/plotneuralnet', 0.542097270488739, 'ml', 0), ('oegedijk/explainerdashboard', 0.54157954454422, 'ml-interpretability', 0), ('tensorlayer/tensorlayer', 0.5410547256469727, 'ml-rl', 3), ('nvlabs/gcvit', 0.5401598811149597, 'diffusion', 1), ('ludwig-ai/ludwig', 0.5391374230384827, 'ml-ops', 7), ('danielegrattarola/spektral', 0.5387458205223083, 'ml-dl', 3), ('keras-team/keras-cv', 0.5374981760978699, 'ml-dl', 1), ('ashleve/lightning-hydra-template', 0.5372906923294067, 'util', 2), ('hysts/pytorch_image_classification', 0.5342903137207031, 'ml-dl', 1), ('tensorflow/addons', 0.5334285497665405, 'ml', 4), ('awslabs/autogluon', 0.5327269434928894, 'ml', 3), ('fepegar/torchio', 0.531164288520813, 'ml-dl', 3), ('microsoft/nni', 0.5304214954376221, 'ml', 5), ('horovod/horovod', 0.5276727080345154, 'ml-ops', 8), ('intel/intel-extension-for-pytorch', 0.5267831683158875, 'perf', 4), ('opentensor/bittensor', 0.5261327028274536, 'ml', 5), ('huggingface/transformers', 0.5258775949478149, 'nlp', 4), ('rafiqhasan/auto-tensorflow', 0.5258046388626099, 'ml-dl', 4), ('skorch-dev/skorch', 0.5238518714904785, 'ml-dl', 2), ('lucidrains/imagen-pytorch', 0.52129065990448, 'ml-dl', 1), ('gradio-app/gradio', 0.520858645439148, 'viz', 2), ('polyaxon/datatile', 0.5207769274711609, 'pandas', 2), ('lightly-ai/lightly', 0.5200084447860718, 'ml', 3), ('albumentations-team/albumentations', 0.5197222828865051, 'ml-dl', 2), ('docarray/docarray', 0.51971834897995, 'data', 3), ('google-research/deeplab2', 0.5186880826950073, 'ml', 0), ('rasbt/machine-learning-book', 0.5182120203971863, 'study', 3), ('cvxgrp/pymde', 0.5167331695556641, 'ml', 2), ('mlflow/mlflow', 0.5155205726623535, 'ml-ops', 3), ('stellargraph/stellargraph', 0.514754056930542, 'graph', 2), ('amanchadha/coursera-deep-learning-specialization', 0.5117756128311157, 'study', 2), ('microsoft/deepspeed', 0.5104838609695435, 'ml-dl', 3), ('pytorchlightning/pytorch-lightning', 0.5080562829971313, 'ml-dl', 4), ('microsoft/torchgeo', 0.5072435140609741, 'gis', 2), ('ray-project/ray', 0.5069729685783386, 'ml-ops', 4), ('interpretml/interpret', 0.5063915848731995, 'ml-interpretability', 2), ('open-mmlab/mmsegmentation', 0.5060480237007141, 'ml', 1), ('apple/coremltools', 0.5053067803382874, 'ml', 4), ('hpcaitech/colossalai', 0.5051214098930359, 'llm', 2), ('tensorly/tensorly', 0.5027545094490051, 'ml-dl', 4), ('mrdbourke/pytorch-deep-learning', 0.5020248889923096, 'study', 3), ('kevinmusgrave/pytorch-metric-learning', 0.5019212365150452, 'ml', 3), ('googlecloudplatform/vertex-ai-samples', 0.5002110004425049, 'ml', 2)]

1

null

21.67

76

65

159

0

2

0

2

76

87

90

1.1

55

423

ml-dl

https://github.com/albumentations-team/albumentations

[]

null

[]

null

albumentations-team/albumentations

albumentations

13,001

1,564

130

Python

https://albumentations.ai

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

albumentations-team

2024-01-13

2018-06-06

294

44.092539

https://avatars.githubusercontent.com/u/57894582?v=4

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

['augmentation', 'deep-learning', 'detection', 'fast-augmentations', 'image-augmentation', 'image-classification', 'image-processing', 'image-segmentation', 'machine-learning', 'object-detection', 'segmentation']

2023-12-07

[('mdbloice/augmentor', 0.6705105900764465, 'ml', 3), ('facebookresearch/augly', 0.6632611751556396, 'data', 0), ('aleju/imgaug', 0.6503161787986755, 'ml', 4), ('open-mmlab/mmediting', 0.5985205769538879, 'ml', 2), ('fepegar/torchio', 0.5927706956863403, 'ml-dl', 3), ('deci-ai/super-gradients', 0.5558651685714722, 'ml-dl', 3), ('project-monai/monai', 0.5541568994522095, 'ml', 1), ('fourthbrain/fastapi-for-machine-learning-live-demo', 0.5520427823066711, 'web', 0), ('visual-layer/fastdup', 0.5445998311042786, 'ml', 5), ('neuralmagic/sparseml', 0.5420981645584106, 'ml-dl', 2), ('lightly-ai/lightly', 0.5409029126167297, 'ml', 2), ('rom1504/clip-retrieval', 0.5307724475860596, 'ml', 1), ('lutzroeder/netron', 0.5197222828865051, 'ml', 2), ('nvlabs/gcvit', 0.5185796618461609, 'diffusion', 2), ('sanster/lama-cleaner', 0.515965461730957, 'ml-dl', 0), ('roboflow/supervision', 0.5144950151443481, 'ml', 4), ('open-mmlab/mmsegmentation', 0.5108982920646667, 'ml', 1), ('google-research/deeplab2', 0.5106143355369568, 'ml', 0), ('kevinmusgrave/pytorch-metric-learning', 0.5062373876571655, 'ml', 2), ('azavea/raster-vision', 0.50620436668396, 'gis', 3), ('keras-team/autokeras', 0.5026241540908813, 'ml-dl', 2), ('kornia/kornia', 0.5021526217460632, 'ml-dl', 3)]

133

3

null

0.35

41

15

68

1

3

1

41

31

90

0.8

55

647

profiling

https://github.com/benfred/py-spy

[]

null

[]

null

benfred/py-spy

py-spy

11,366

429

112

Rust

null

Sampling profiler for Python programs

benfred

2024-01-13

2018-08-01

286

39.62251

null

Sampling profiler for Python programs

['performance-analysis', 'profiler', 'profiling']

2023-12-16

[('pythonspeed/filprofiler', 0.7144114971160889, 'profiling', 0), ('pyutils/line_profiler', 0.6891393065452576, 'profiling', 0), ('sumerc/yappi', 0.6047118902206421, 'profiling', 0), ('p403n1x87/austin', 0.5970548987388611, 'profiling', 1), ('joerick/pyinstrument', 0.5834751129150391, 'profiling', 1), ('pympler/pympler', 0.5802413821220398, 'perf', 0), ('klen/py-frameworks-bench', 0.5661771297454834, 'perf', 0), ('jiffyclub/snakeviz', 0.5489193797111511, 'profiling', 0), ('plasma-umass/scalene', 0.533981204032898, 'profiling', 3), ('pythonprofilers/memory_profiler', 0.5219977498054504, 'profiling', 0), ('csurfer/pyheat', 0.5209768414497375, 'profiling', 1), ('lcompilers/lpython', 0.5141026377677917, 'util', 0), ('google/pytype', 0.5136662721633911, 'typing', 0), ('nedbat/coveragepy', 0.5097211599349976, 'testing', 0), ('ionelmc/pytest-benchmark', 0.5037754774093628, 'testing', 0)]

37

3

null

0.46

48

16

66

1

0

6

48

41

90

0.9

55

1,119

data

https://github.com/coleifer/peewee

[]

null

[]

null

coleifer/peewee

peewee

10,573

1,373

198

Python

http://docs.peewee-orm.com/

a small, expressive orm -- supports postgresql, mysql, sqlite and cockroachdb

coleifer

2024-01-13

2010-10-11

694

15.231735

null

a small, expressive orm -- supports postgresql, mysql, sqlite and cockroachdb

['dank', 'gametight', 'peewee', 'sqlite']

2024-01-05

[('mcfunley/pugsql', 0.6096048951148987, 'data', 0), ('ibis-project/ibis', 0.5938148498535156, 'data', 1), ('tiangolo/sqlmodel', 0.5841237306594849, 'data', 0), ('tiangolo/full-stack-fastapi-postgresql', 0.5561289191246033, 'template', 0), ('piccolo-orm/piccolo_admin', 0.5553250908851624, 'data', 1), ('aio-libs/aiopg', 0.5507586002349854, 'data', 0), ('tobymao/sqlglot', 0.5414004325866699, 'data', 1), ('airbytehq/airbyte', 0.53973788022995, 'data', 0), ('simonw/datasette', 0.5180539488792419, 'data', 1), ('zenodo/zenodo', 0.5084249377250671, 'util', 0), ('lancedb/lancedb', 0.5083345770835876, 'data', 0)]

153

3

null

1.83

42

161

0

5

14

5

42

84

90

2

55

5

web

https://github.com/benoitc/gunicorn

[]

null

[]

null

benoitc/gunicorn

gunicorn

9,324

1,706

225

Python

http://www.gunicorn.org

gunicorn 'Green Unicorn' is a WSGI HTTP Server for UNIX, fast clients and sleepy applications.

benoitc

2024-01-14

2009-11-30

739

12.614612

null

gunicorn 'Green Unicorn' is a WSGI HTTP Server for UNIX, fast clients and sleepy applications.

['http', 'http-server', 'wsgi', 'wsgi-server']

2024-01-05

[('pallets/werkzeug', 0.6659462451934814, 'web', 2), ('pylons/waitress', 0.6345184445381165, 'web', 2), ('bottlepy/bottle', 0.6153336763381958, 'web', 1), ('cherrypy/cherrypy', 0.5961728096008301, 'web', 2), ('pallets/flask', 0.5726903676986694, 'web', 1), ('pylons/pyramid', 0.5611777305603027, 'web', 1), ('encode/uvicorn', 0.5551705360412598, 'web', 2), ('neoteroi/blacksheep', 0.542283296585083, 'web', 2), ('encode/httpx', 0.5388432145118713, 'web', 1), ('falconry/falcon', 0.5321671366691589, 'web', 2), ('pylons/webob', 0.5041623711585999, 'web', 1), ('klen/muffin', 0.5010045766830444, 'web', 0)]

417

6

null

1.42

162

80

172

0

3

7

3

162

190

90

1.2

55

1,332

nlp

https://github.com/google/sentencepiece

['word-segmentation', 'tokeniser']

null

[]

1

null

google/sentencepiece

sentencepiece

8,799

1,078

125

C++

null

Unsupervised text tokenizer for Neural Network-based text generation.

google

2024-01-14

2017-03-07

360

24.441667

https://avatars.githubusercontent.com/u/1342004?v=4

Unsupervised text tokenizer for Neural Network-based text generation.

['natural-language-processing', 'neural-machine-translation', 'word-segmentation']

['natural-language-processing', 'neural-machine-translation', 'tokeniser', 'word-segmentation']

2024-01-14

[('minimaxir/textgenrnn', 0.6446799635887146, 'nlp', 0), ('huggingface/text-generation-inference', 0.607265830039978, 'llm', 0), ('google-research/electra', 0.5957339406013489, 'ml-dl', 0), ('lucidrains/deep-daze', 0.5594016909599304, 'ml', 0), ('sharonzhou/long_stable_diffusion', 0.5528421401977539, 'diffusion', 0), ('minimaxir/aitextgen', 0.5358452796936035, 'llm', 0), ('infinitylogesh/mutate', 0.5126572847366333, 'nlp', 0)]

81

4

null

1.31

65

46

83

0

3

4

3

65

68

90

1

55

1,195

llm

https://github.com/thudm/codegeex

[]

null

[]

null

thudm/codegeex

CodeGeeX

7,468

525

78

Python

https://codegeex.cn

CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023)

thudm

2024-01-13

2022-09-17

71

104.552

https://avatars.githubusercontent.com/u/48590610?v=4

CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023)

['code-generation', 'pretrained-models', 'tools']

2023-08-04

[('salesforce/codet5', 0.6897627115249634, 'nlp', 1), ('salesforce/codegen', 0.6133092045783997, 'nlp', 0), ('bigcode-project/starcoder', 0.5817055106163025, 'llm', 1), ('ctlllll/llm-toolmaker', 0.5676085948944092, 'llm', 0), ('conceptofmind/toolformer', 0.5580187439918518, 'llm', 0), ('asottile/pyupgrade', 0.5523767471313477, 'util', 0), ('neulab/prompt2model', 0.525926411151886, 'llm', 0), ('microsoft/pycodegpt', 0.5184867978096008, 'llm', 1), ('yueyu1030/attrprompt', 0.510209858417511, 'llm', 0), ('guidance-ai/guidance', 0.5090668201446533, 'llm', 0), ('pre-commit/pre-commit', 0.5082143545150757, 'util', 0), ('lianjiatech/belle', 0.5078340172767639, 'llm', 0), ('ravenscroftj/turbopilot', 0.5072124600410461, 'llm', 0), ('lupantech/chameleon-llm', 0.5048568844795227, 'llm', 0), ('juncongmoo/pyllama', 0.503732442855835, 'llm', 0), ('salesforce/xgen', 0.5032574534416199, 'llm', 0), ('thudm/glm-130b', 0.5032495856285095, 'llm', 0), ('openai/finetune-transformer-lm', 0.5009891390800476, 'llm', 0), ('yizhongw/self-instruct', 0.5008969902992249, 'llm', 0)]

13

6

null

0.9

25

2

16

5

0

25

15

90

0.6

55

1,372

web

https://github.com/reactive-python/reactpy

[]

ReactPy is a library for building user interfaces in Python without Javascript

[]

null

reactive-python/reactpy

reactpy

7,438

363

58

Python

https://reactpy.dev

It's React, but in Python

reactive-python

2024-01-13

2019-02-19

258

28.829457

https://avatars.githubusercontent.com/u/106191177?v=4

It's React, but in Python

['javascript', 'react', 'reactpy']

2023-12-28

[('r0x0r/pywebview', 0.5532059073448181, 'gui', 1), ('webpy/webpy', 0.5520175695419312, 'web', 0), ('pyodide/pyodide', 0.5306482911109924, 'util', 0), ('urwid/urwid', 0.5233248472213745, 'term', 0)]

21

4

null

2.15

35

12

60

1

12

23

12

35

50

90

1.4

55

680

util

https://github.com/py-pdf/pypdf2

[]

null

[]

null

py-pdf/pypdf2

pypdf

6,900

1,301

148

Python

https://pypdf.readthedocs.io/en/latest/

A pure-python PDF library capable of splitting, merging, cropping, and transforming the pages of PDF files

py-pdf

2024-01-14

2012-01-06

629

10.959837

https://avatars.githubusercontent.com/u/102914013?v=4

A pure-python PDF library capable of splitting, merging, cropping, and transforming the pages of PDF files

['help-wanted', 'pdf', 'pdf-documents', 'pdf-manipulation', 'pdf-parser', 'pdf-parsing', 'pypdf2']

2024-01-11

[('pyfpdf/fpdf2', 0.6898808479309082, 'util', 1), ('jorisschellekens/borb', 0.6551130414009094, 'util', 1), ('camelot-dev/camelot', 0.6539286971092224, 'util', 0), ('pypdfium2-team/pypdfium2', 0.6358337998390198, 'util', 2), ('pdfminer/pdfminer.six', 0.5491688847541809, 'util', 1), ('unstructured-io/pipeline-paddleocr', 0.5316691398620605, 'data', 1)]

216

1

null

8.63

184

124

146

0

37

9

37

184

483

90

2.6

55

1,492

llm

https://github.com/bigcode-project/starcoder

['code-generation']

null

[]

null

bigcode-project/starcoder

starcoder

6,776

476

65

Python

null

Home of StarCoder: fine-tuning & inference!

bigcode-project

2024-01-13

2023-04-24

40

168.797153

https://avatars.githubusercontent.com/u/110470554?v=4

Home of StarCoder: fine-tuning & inference!

[]

['code-generation']

2023-06-29

[('salesforce/codegen', 0.601254940032959, 'nlp', 0), ('huggingface/text-generation-inference', 0.5950606465339661, 'llm', 0), ('salesforce/codet5', 0.5859589576721191, 'nlp', 1), ('openai/image-gpt', 0.5846189260482788, 'llm', 0), ('thudm/codegeex', 0.5817055106163025, 'llm', 1), ('bytedance/lightseq', 0.5453761219978333, 'nlp', 0), ('microsoft/pycodegpt', 0.5438132882118225, 'llm', 1), ('deepmind/deepmind-research', 0.5220165252685547, 'ml', 0), ('facebookresearch/codellama', 0.5031982064247131, 'llm', 0)]

8

3

null

1.31

16

1

9

7

0

16

10

90

0.6

55

20

typing

https://github.com/facebook/pyre-check

['code-quality']

null

[]

null

facebook/pyre-check

pyre-check

6,597

477

110

Python

https://pyre-check.org/

Performant type-checking for python.

facebook

2024-01-12

2017-11-10

324

20.325264

https://avatars.githubusercontent.com/u/69631?v=4

Performant type-checking for python.

['abstract-interpretation', 'code-quality', 'control-flow-analysis', 'ocaml', 'program-analysis', 'security', 'static-analysis', 'taint-analysis', 'type-check', 'typechecker']

2024-01-12

[('agronholm/typeguard', 0.8064729571342468, 'typing', 2), ('google/pytype', 0.7848848104476929, 'typing', 3), ('microsoft/pyright', 0.7650810480117798, 'typing', 2), ('instagram/monkeytype', 0.6643034815788269, 'typing', 1), ('python/mypy', 0.628227949142456, 'typing', 2), ('pydantic/pydantic', 0.6196001768112183, 'util', 0), ('patrick-kidger/torchtyping', 0.6189740300178528, 'typing', 0), ('rubik/radon', 0.6015112400054932, 'util', 1), ('landscapeio/prospector', 0.5935577154159546, 'util', 0), ('pycqa/mccabe', 0.5869566202163696, 'util', 0), ('pytoolz/toolz', 0.5858352184295654, 'util', 0), ('tiangolo/typer', 0.5768271088600159, 'term', 0), ('nedbat/coveragepy', 0.5666431784629822, 'testing', 0), ('pyupio/safety', 0.5607929229736328, 'security', 1), ('xrudelis/pytrait', 0.5590521693229675, 'util', 0), ('strawberry-graphql/strawberry', 0.5584018230438232, 'web', 0), ('python/typeshed', 0.5521007180213928, 'typing', 1), ('eugeneyan/python-collab-template', 0.5504177212715149, 'template', 0), ('aswinnnn/pyscan', 0.5478062033653259, 'security', 2), ('marshmallow-code/marshmallow', 0.5461035966873169, 'util', 0), ('pympler/pympler', 0.5445180535316467, 'perf', 0), ('pyston/pyston', 0.5409777760505676, 'util', 0), ('python-odin/odin', 0.5255442261695862, 'util', 0), ('pypy/pypy', 0.5224389433860779, 'util', 0), ('psf/black', 0.5206736922264099, 'util', 1), ('python-rope/rope', 0.5157984495162964, 'util', 0), ('python/cpython', 0.5143840312957764, 'util', 0), ('grantjenks/blue', 0.5125738382339478, 'util', 1), ('gaogaotiantian/viztracer', 0.5102528929710388, 'profiling', 0), ('pyeve/cerberus', 0.5100794434547424, 'data', 0), ('scikit-mobility/scikit-mobility', 0.5081936120986938, 'gis', 0), ('astral-sh/ruff', 0.5057628154754639, 'util', 2), ('pycqa/flake8', 0.5048815608024597, 'util', 2), ('facebookincubator/bowler', 0.5039924383163452, 'util', 0), ('cython/cython', 0.5014179944992065, 'util', 0)]

254

2

null

29.19

13

4

75

0

1

14

1

13

21

90

1.6

55

70

util

https://github.com/pygithub/pygithub

[]

null

[]

null

pygithub/pygithub

PyGithub

6,469

1,713

111

Python

https://pygithub.readthedocs.io/

Typed interactions with the GitHub API v3

pygithub

2024-01-13

2012-02-25

622

10.39316

https://avatars.githubusercontent.com/u/11288996?v=4

Typed interactions with the GitHub API v3

['github', 'github-api', 'pygithub']

2024-01-01

[('fastai/ghapi', 0.5488420724868774, 'util', 2)]

346

4

null

4

103

47

145

0

10

9

10

103

179

90

1.7

55

1,814

study

https://github.com/mrdbourke/pytorch-deep-learning

[]

null

[]

null

mrdbourke/pytorch-deep-learning

pytorch-deep-learning

6,384

2,082

88

Jupyter Notebook

https://learnpytorch.io

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.

mrdbourke

2024-01-14

2021-10-19

119

53.647059

null

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.

['deep-learning', 'machine-learning', 'pytorch']

2024-01-11

[('pytorch/ignite', 0.7811650037765503, 'ml-dl', 3), ('mrdbourke/tensorflow-deep-learning', 0.7342724800109863, 'study', 1), ('skorch-dev/skorch', 0.6955669522285461, 'ml-dl', 2), ('pyg-team/pytorch_geometric', 0.6894313097000122, 'ml-dl', 2), ('rasbt/machine-learning-book', 0.6849406957626343, 'study', 3), ('mrdbourke/zero-to-mastery-ml', 0.676668107509613, 'study', 2), ('nvidia/apex', 0.6514618396759033, 'ml-dl', 0), ('intel/intel-extension-for-pytorch', 0.6339874267578125, 'perf', 3), ('ageron/handson-ml2', 0.633056104183197, 'ml', 0), ('denys88/rl_games', 0.6325936913490295, 'ml-rl', 2), ('udacity/deep-learning-v2-pytorch', 0.6218847632408142, 'study', 2), ('d2l-ai/d2l-en', 0.6161856055259705, 'study', 3), ('pytorch/rl', 0.6149892210960388, 'ml-rl', 2), ('xl0/lovely-tensors', 0.613914966583252, 'ml-dl', 2), ('ashleve/lightning-hydra-template', 0.605148196220398, 'util', 2), ('udlbook/udlbook', 0.6033921837806702, 'study', 1), ('karpathy/micrograd', 0.602993369102478, 'study', 0), ('allenai/allennlp', 0.6028923988342285, 'nlp', 2), ('graykode/nlp-tutorial', 0.6003298163414001, 'study', 1), ('thu-ml/tianshou', 0.5997803211212158, 'ml-rl', 1), ('tensorlayer/tensorlayer', 0.5996901392936707, 'ml-rl', 1), ('intellabs/bayesian-torch', 0.5984524488449097, 'ml', 2), ('nicolas-chaulet/torch-points3d', 0.5965690016746521, 'ml', 0), ('facebookresearch/pytorch3d', 0.5950154066085815, 'ml-dl', 0), ('keras-team/keras', 0.5936383008956909, 'ml-dl', 3), ('pytorch/captum', 0.5934852361679077, 'ml-interpretability', 0), ('fchollet/deep-learning-with-python-notebooks', 0.5927961468696594, 'study', 0), ('rentruewang/koila', 0.5876379609107971, 'ml', 3), ('davidadsp/generative_deep_learning_2nd_edition', 0.5829065442085266, 'study', 2), ('openai/spinningup', 0.580998420715332, 'study', 0), ('christoschristofidis/awesome-deep-learning', 0.5786244869232178, 'study', 2), ('huggingface/accelerate', 0.5736592411994934, 'ml', 0), ('pyro-ppl/pyro', 0.5717006325721741, 'ml-dl', 3), ('pytorch/data', 0.5634875893592834, 'data', 0), ('rasbt/deeplearning-models', 0.5607303977012634, 'ml-dl', 0), ('lucidrains/imagen-pytorch', 0.5554819703102112, 'ml-dl', 1), ('keras-rl/keras-rl', 0.554979681968689, 'ml-rl', 1), ('huggingface/transformers', 0.5548473596572876, 'nlp', 3), ('lightly-ai/lightly', 0.5538014769554138, 'ml', 3), ('tensorflow/tensor2tensor', 0.5526059865951538, 'ml', 2), ('horovod/horovod', 0.548136830329895, 'ml-ops', 3), ('ggerganov/ggml', 0.5461394190788269, 'ml', 1), ('pytorch/torchrec', 0.5445482730865479, 'ml-dl', 2), ('blackhc/toma', 0.5438900589942932, 'ml-dl', 2), ('salesforce/blip', 0.5360457897186279, 'diffusion', 0), ('amanchadha/coursera-deep-learning-specialization', 0.5357545614242554, 'study', 1), ('nvidia/deeplearningexamples', 0.5341781973838806, 'ml-dl', 2), ('humancompatibleai/imitation', 0.5296970009803772, 'ml-rl', 0), ('arogozhnikov/einops', 0.528740644454956, 'ml-dl', 2), ('laekov/fastmoe', 0.5278257131576538, 'ml', 0), ('hazyresearch/hgcn', 0.5278249979019165, 'ml', 0), ('huggingface/huggingface_hub', 0.5265445113182068, 'ml', 3), ('kshitij12345/torchnnprofiler', 0.5249190926551819, 'profiling', 0), ('tensorflow/tensorflow', 0.5236486196517944, 'ml-dl', 2), ('aistream-peelout/flow-forecast', 0.5234374403953552, 'time-series', 2), ('uber/petastorm', 0.5223989486694336, 'data', 3), ('karpathy/mingpt', 0.5222852230072021, 'llm', 0), ('microsoft/jarvis', 0.5219099521636963, 'llm', 2), ('nvlabs/gcvit', 0.520950198173523, 'diffusion', 1), ('pytorch/botorch', 0.5209388136863708, 'ml-dl', 0), ('rasbt/stat453-deep-learning-ss20', 0.5198850631713867, 'study', 0), ('whitead/dmol-book', 0.5192140340805054, 'ml-dl', 1), ('patchy631/machine-learning', 0.5156992673873901, 'ml', 0), ('neuralmagic/sparseml', 0.5144563317298889, 'ml-dl', 1), ('nyandwi/modernconvnets', 0.5134690999984741, 'ml-dl', 0), ('hysts/pytorch_image_classification', 0.5127461552619934, 'ml-dl', 1), ('dmlc/dgl', 0.5118030905723572, 'ml-dl', 1), ('determined-ai/determined', 0.5115607380867004, 'ml-ops', 3), ('mosaicml/composer', 0.5073535442352295, 'ml-dl', 3), ('rafiqhasan/auto-tensorflow', 0.5060444474220276, 'ml-dl', 1), ('cvxgrp/pymde', 0.5034160017967224, 'ml', 2), ('optimalscale/lmflow', 0.503092348575592, 'llm', 2), ('lutzroeder/netron', 0.5020248889923096, 'ml', 3), ('microsoft/deepspeed', 0.5005961656570435, 'ml-dl', 3), ('google-research/deeplab2', 0.5000344514846802, 'ml', 0)]

42

3

null

2.42

41

9

27

0

41

27

90

0.7

55

1,177

diffusion

https://github.com/openai/consistency_models

[]

null

[]

null

openai/consistency_models

consistency_models

5,787

379

60

Python

null

Official repo for consistency models.

openai

2024-01-13

2023-02-26

48

119.849112

https://avatars.githubusercontent.com/u/14957082?v=4

Official repo for consistency models.

[]

2023-08-12

[]

9

7

null

0.23

18

1

11

5

0

18

16

90

0.9

55

1,081

util

https://github.com/buildbot/buildbot

[]

null

[]

null

buildbot/buildbot

buildbot

5,127

1,655

199

Python

https://www.buildbot.net

Python-based continuous integration testing framework; your pull requests are more than welcome!

buildbot

2024-01-14

2010-07-06

708

7.241525

https://avatars.githubusercontent.com/u/324515?v=4

Python-based continuous integration testing framework; your pull requests are more than welcome!

['ci', 'ci-framework', 'continuous-integration']

2024-01-09

[('eleutherai/pyfra', 0.6259655952453613, 'ml', 0), ('nedbat/coveragepy', 0.57981938123703, 'testing', 0), ('wolever/parameterized', 0.5751279592514038, 'testing', 0), ('willmcgugan/textual', 0.5555017590522766, 'term', 0), ('masoniteframework/masonite', 0.549967885017395, 'web', 0), ('cobrateam/splinter', 0.5403817296028137, 'testing', 0), ('tox-dev/tox', 0.5279530882835388, 'testing', 1), ('taverntesting/tavern', 0.5253430604934692, 'testing', 0), ('getsentry/responses', 0.5227794647216797, 'testing', 0), ('ethereum/web3.py', 0.5160036087036133, 'crypto', 0), ('google/gin-config', 0.5084891319274902, 'util', 0), ('pytest-dev/pytest-xdist', 0.5035778880119324, 'testing', 0)]

856

5

null

22.69

255

203

165

0

6

13

6

255

235

90

0.9

55

98

jupyter

https://github.com/voila-dashboards/voila

[]

null

[]

null

voila-dashboards/voila

voila

5,051

487

77

Python

https://voila.readthedocs.io

Voilà turns Jupyter notebooks into standalone web applications

voila-dashboards

2024-01-14

2018-08-21

284

17.785211

https://avatars.githubusercontent.com/u/55792893?v=4

Voilà turns Jupyter notebooks into standalone web applications

['dashboarding', 'jupyter', 'jupyter-notebook', 'jupyterlab-extension']

2024-01-11

[('jupyterlab/jupyterlab-desktop', 0.7262636423110962, 'jupyter', 2), ('jupyter-widgets/ipywidgets', 0.7114137411117554, 'jupyter', 1), ('jupyter/notebook', 0.6948908567428589, 'jupyter', 2), ('jupyterlite/jupyterlite', 0.6913954615592957, 'jupyter', 2), ('aws/graph-notebook', 0.6807038187980652, 'jupyter', 2), ('mwouts/jupytext', 0.6650576591491699, 'jupyter', 2), ('jupyter/nbviewer', 0.6448253989219666, 'jupyter', 2), ('vizzuhq/ipyvizzu', 0.6425187587738037, 'jupyter', 2), ('maartenbreddels/ipyvolume', 0.6421133279800415, 'jupyter', 2), ('cohere-ai/notebooks', 0.60094153881073, 'llm', 0), ('jupyter/nbformat', 0.5947333574295044, 'jupyter', 0), ('holoviz/panel', 0.5938263535499573, 'viz', 1), ('jupyter/nbconvert', 0.5891522169113159, 'jupyter', 0), ('xiaohk/stickyland', 0.5852877497673035, 'jupyter', 2), ('jupyter/nbdime', 0.5848777890205383, 'jupyter', 3), ('jupyter-widgets/ipyleaflet', 0.5810590386390686, 'gis', 2), ('plotly/dash', 0.580794095993042, 'viz', 1), ('pallets/flask', 0.5802770256996155, 'web', 0), ('jupyterlab/jupyterlab', 0.5699175596237183, 'jupyter', 1), ('webpy/webpy', 0.5608404278755188, 'web', 0), ('ipython/ipyparallel', 0.5572918057441711, 'perf', 1), ('jupyter-lsp/jupyterlab-lsp', 0.5473379492759705, 'jupyter', 3), ('plotly/plotly.py', 0.5468341112136841, 'viz', 1), ('mamba-org/gator', 0.5456347465515137, 'jupyter', 2), ('reflex-dev/reflex', 0.5454056859016418, 'web', 0), ('bloomberg/ipydatagrid', 0.5380343794822693, 'jupyter', 1), ('tkrabel/bamboolib', 0.5368069410324097, 'pandas', 1), ('bokeh/bokeh', 0.5361472368240356, 'viz', 1), ('ipython/ipykernel', 0.5356465578079224, 'util', 2), ('quantopian/qgrid', 0.5343106985092163, 'jupyter', 0), ('willmcgugan/textual', 0.5331439971923828, 'term', 0), ('giswqs/mapwidget', 0.5279869437217712, 'gis', 1), ('rapidsai/jupyterlab-nvdashboard', 0.5271745920181274, 'jupyter', 0), ('masoniteframework/masonite', 0.5220005512237549, 'web', 0), ('klen/muffin', 0.5211663246154785, 'web', 0), ('r0x0r/pywebview', 0.5208461880683899, 'gui', 0), ('opengeos/leafmap', 0.5204005241394043, 'gis', 2), ('computationalmodelling/nbval', 0.5194684267044067, 'jupyter', 1), ('fchollet/deep-learning-with-python-notebooks', 0.5183944702148438, 'study', 0), ('jakevdp/pythondatasciencehandbook', 0.5165765881538391, 'study', 1), ('bottlepy/bottle', 0.5106417536735535, 'web', 0), ('pysimplegui/pysimplegui', 0.5095065236091614, 'gui', 0), ('cherrypy/cherrypy', 0.5070238709449768, 'web', 0), ('seleniumbase/seleniumbase', 0.5014607906341553, 'testing', 0)]

68

4

null

1.71

41

22

66

0

18

32

18

41

66

90

1.6

55

257

crypto

https://github.com/ethereum/web3.py

[]

null

[]

1

null

ethereum/web3.py

web3.py

4,591

1,654

119

Python

http://web3py.readthedocs.io

A python interface for interacting with the Ethereum blockchain and ecosystem.

ethereum

2024-01-14

2016-04-14

406

11.288022

https://avatars.githubusercontent.com/u/6250754?v=4

A python interface for interacting with the Ethereum blockchain and ecosystem.

[]

2024-01-10

[('primal100/pybitcointools', 0.6811222434043884, 'crypto', 0), ('ethereum/py-evm', 0.6437891721725464, 'crypto', 0), ('gbeced/basana', 0.6058024168014526, 'finance', 0), ('1200wd/bitcoinlib', 0.6057431101799011, 'crypto', 0), ('willmcgugan/textual', 0.5721923112869263, 'term', 0), ('gbeced/pyalgotrade', 0.570094883441925, 'finance', 0), ('pyston/pyston', 0.5668970942497253, 'util', 0), ('masoniteframework/masonite', 0.5657337307929993, 'web', 0), ('eleutherai/pyfra', 0.5655627250671387, 'ml', 0), ('bottlepy/bottle', 0.5624367594718933, 'web', 0), ('man-c/pycoingecko', 0.5624127388000488, 'crypto', 0), ('hydrosquall/tiingo-python', 0.5618115067481995, 'finance', 0), ('simple-salesforce/simple-salesforce', 0.5512309670448303, 'data', 0), ('hoffstadt/dearpygui', 0.5474371314048767, 'gui', 0), ('replicate/replicate-python', 0.5461574792861938, 'ml', 0), ('urwid/urwid', 0.5449756979942322, 'term', 0), ('robcarver17/pysystemtrade', 0.5425991415977478, 'finance', 0), ('falconry/falcon', 0.540778636932373, 'web', 0), ('requests/toolbelt', 0.5374890565872192, 'util', 0), ('pynamodb/pynamodb', 0.536690890789032, 'data', 0), ('pmaji/crypto-whale-watching-app', 0.5342921614646912, 'crypto', 0), ('secdev/scapy', 0.5224668383598328, 'util', 0), ('buildbot/buildbot', 0.5160036087036133, 'util', 0), ('pallets/flask', 0.5149424076080322, 'web', 0), ('amzn/ion-python', 0.5136985778808594, 'data', 0), ('scrapy/scrapy', 0.5123814344406128, 'data', 0), ('pytoolz/toolz', 0.5079506039619446, 'util', 0), ('webpy/webpy', 0.5061323046684265, 'web', 0), ('trailofbits/pip-audit', 0.5048879981040955, 'security', 0), ('nasdaq/data-link-python', 0.5034674406051636, 'finance', 0), ('cherrypy/cherrypy', 0.5029838681221008, 'web', 0), ('encode/httpx', 0.5025968551635742, 'web', 0), ('snyk-labs/pysnyk', 0.5023728013038635, 'security', 0)]

249

4

null

9.17

106

76

94

0

27

106

104

90

1

55

1,842

llm

https://github.com/langchain-ai/chat-langchain

['rag', 'question-answering', 'docs']

Locally hosted chatbot specifically focused on question answering over the LangChain documentation

[]

null

langchain-ai/chat-langchain

chat-langchain

4,229

1,008

46

Python

https://chat.langchain.com

null

langchain-ai

2024-01-13

2023-01-16

54

78.108179

https://avatars.githubusercontent.com/u/126733545?v=4

Locally hosted chatbot specifically focused on question answering over the LangChain documentation

[]

['docs', 'question-answering', 'rag']

2024-01-11

[('lm-sys/fastchat', 0.628669023513794, 'llm', 0), ('togethercomputer/openchatkit', 0.6002198457717896, 'nlp', 0), ('embedchain/embedchain', 0.5953378677368164, 'llm', 0), ('nomic-ai/gpt4all', 0.594020426273346, 'llm', 0), ('mayooear/gpt4-pdf-chatbot-langchain', 0.5839036107063293, 'llm', 0), ('gunthercox/chatterbot-corpus', 0.5771211981773376, 'nlp', 0), ('hwchase17/langchain', 0.5708911418914795, 'llm', 0), ('openai/chatgpt-retrieval-plugin', 0.5608171820640564, 'llm', 0), ('rcgai/simplyretrieve', 0.5566864013671875, 'llm', 0), ('gkamradt/langchain-tutorials', 0.5390220284461975, 'study', 0), ('larsbaunwall/bricky', 0.5356094837188721, 'llm', 0), ('minimaxir/simpleaichat', 0.5350149273872375, 'llm', 0), ('fasteval/fasteval', 0.534351110458374, 'llm', 0), ('weaviate/verba', 0.5274889469146729, 'llm', 0), ('openlmlab/moss', 0.5243722200393677, 'llm', 0), ('deeppavlov/deeppavlov', 0.5239380598068237, 'nlp', 1), ('blinkdl/chatrwkv', 0.521385908126831, 'llm', 0), ('mlc-ai/web-llm', 0.5200137495994568, 'llm', 0), ('run-llama/rags', 0.5135616064071655, 'llm', 1), ('rasahq/rasa', 0.5066604614257812, 'llm', 0), ('thudm/chatglm2-6b', 0.5037407875061035, 'llm', 0), ('killianlucas/open-interpreter', 0.5030243396759033, 'llm', 0)]

16

1

null

2.63

51

35

12

0

51

56

90

1.1

55

1,239

llm

https://github.com/togethercomputer/redpajama-data

[]

null

[]

null

togethercomputer/redpajama-data

RedPajama-Data

4,058

321

78

Python

null

The RedPajama-Data repository contains code for preparing large datasets for training large language models.

togethercomputer

2024-01-13

2023-04-14

41

97.61512

https://avatars.githubusercontent.com/u/109101822?v=4

The RedPajama-Data repository contains code for preparing large datasets for training large language models.

[]

2023-12-27

[('hannibal046/awesome-llm', 0.6528944969177246, 'study', 0), ('yueyu1030/attrprompt', 0.6486657857894897, 'llm', 0), ('freedomintelligence/llmzoo', 0.6302767992019653, 'llm', 0), ('bigscience-workshop/biomedical', 0.6301681995391846, 'data', 0), ('eleutherai/the-pile', 0.6279685497283936, 'data', 0), ('cg123/mergekit', 0.6147141456604004, 'llm', 0), ('infinitylogesh/mutate', 0.6091659069061279, 'nlp', 0), ('ai21labs/lm-evaluation', 0.60612553358078, 'llm', 0), ('databrickslabs/dolly', 0.5899375677108765, 'llm', 0), ('lm-sys/fastchat', 0.5893017053604126, 'llm', 0), ('huggingface/text-generation-inference', 0.5783564448356628, 'llm', 0), ('tatsu-lab/stanford_alpaca', 0.5778451561927795, 'llm', 0), ('ctlllll/llm-toolmaker', 0.5702430605888367, 'llm', 0), ('lianjiatech/belle', 0.5700726509094238, 'llm', 0), ('openlm-research/open_llama', 0.5621833801269531, 'llm', 0), ('microsoft/lora', 0.5614542365074158, 'llm', 0), ('next-gpt/next-gpt', 0.5498401522636414, 'llm', 0), ('openai/finetune-transformer-lm', 0.5497167706489563, 'llm', 0), ('salesforce/xgen', 0.5379053950309753, 'llm', 0), ('prefecthq/langchain-prefect', 0.5340298414230347, 'llm', 0), ('bytedance/lightseq', 0.5332623720169067, 'nlp', 0), ('huawei-noah/pretrained-language-model', 0.5328022837638855, 'nlp', 0), ('juncongmoo/pyllama', 0.5303771495819092, 'llm', 0), ('baichuan-inc/baichuan-13b', 0.5299484729766846, 'llm', 0), ('srush/minichain', 0.5224243998527527, 'llm', 0), ('lupantech/chameleon-llm', 0.5191816687583923, 'llm', 0), ('princeton-nlp/alce', 0.5159098505973816, 'llm', 0), ('microsoft/autogen', 0.5106208920478821, 'llm', 0), ('microsoft/unilm', 0.5096539855003357, 'nlp', 0), ('ravenscroftj/turbopilot', 0.5085808038711548, 'llm', 0), ('oobabooga/text-generation-webui', 0.5050533413887024, 'llm', 0), ('optimalscale/lmflow', 0.5022752285003662, 'llm', 0)]

8

3

null

0.54

28

18

9

1

0

28

39

90

1.4

55

504

ml-ops

https://github.com/adap/flower

[]

null

[]

null

adap/flower

flower

3,479

686

33

Python

https://flower.dev

Flower: A Friendly Federated Learning Framework

adap

2024-01-14

2020-02-17

206

16.876646

https://avatars.githubusercontent.com/u/57905187?v=4

Flower: A Friendly Federated Learning Framework

['ai', 'android', 'artificial-intelligence', 'cpp', 'deep-learning', 'federated-analytics', 'federated-learning', 'federated-learning-framework', 'fleet-intelligence', 'fleet-learning', 'flower', 'framework', 'grpc', 'ios', 'machine-learning', 'pytorch', 'raspberry-pi', 'scikit-learn', 'tensorflow']

2024-01-08

[('nevronai/metisfl', 0.8411728739738464, 'ml', 6), ('jonasgeiping/breaching', 0.6508305668830872, 'ml', 3), ('horovod/horovod', 0.6284599304199219, 'ml-ops', 4), ('nccr-itmo/fedot', 0.618629515171051, 'ml-ops', 1), ('tensorflow/tensorflow', 0.6108560562133789, 'ml-dl', 3), ('mlflow/mlflow', 0.5906698107719421, 'ml-ops', 2), ('determined-ai/determined', 0.5839700698852539, 'ml-ops', 4), ('explosion/thinc', 0.5687860250473022, 'ml-dl', 6), ('onnx/onnx', 0.5646280646324158, 'ml', 5), ('polyaxon/polyaxon', 0.5568473935127258, 'ml-ops', 5), ('ml-tooling/opyrator', 0.5547651648521423, 'viz', 1), ('ai4finance-foundation/finrl', 0.551112949848175, 'finance', 0), ('gradio-app/gradio', 0.5504258871078491, 'viz', 2), ('merantix-momentum/squirrel-core', 0.5503032803535461, 'ml', 5), ('microsoft/onnxruntime', 0.5461448431015015, 'ml', 5), ('ludwig-ai/ludwig', 0.533837080001831, 'ml-ops', 3), ('alpa-projects/alpa', 0.5309455990791321, 'ml-dl', 2), ('tensorlayer/tensorlayer', 0.5287955403327942, 'ml-rl', 3), ('uber/petastorm', 0.5249413847923279, 'data', 4), ('nvidia/deeplearningexamples', 0.5243560671806335, 'ml-dl', 3), ('eventual-inc/daft', 0.5243489146232605, 'pandas', 2), ('bentoml/bentoml', 0.519675612449646, 'ml-ops', 3), ('microsoft/deepspeed', 0.5188344120979309, 'ml-dl', 3), ('apache/incubator-mxnet', 0.5179499387741089, 'ml-dl', 0), ('aiqc/aiqc', 0.5167785882949829, 'ml-ops', 0), ('googlecloudplatform/vertex-ai-samples', 0.5161627531051636, 'ml', 1), ('aimhubio/aim', 0.5154430270195007, 'ml-ops', 4), ('tensorly/tensorly', 0.5153002142906189, 'ml-dl', 3), ('operand/agency', 0.5125753283500671, 'llm', 4), ('dylanhogg/awesome-python', 0.510422945022583, 'study', 2), ('opentensor/bittensor', 0.5103121399879456, 'ml', 4), ('pytorchlightning/pytorch-lightning', 0.5078296065330505, 'ml-dl', 5), ('koaning/human-learn', 0.5073186755180359, 'data', 2), ('aws/sagemaker-python-sdk', 0.506871223449707, 'ml', 3), ('d2l-ai/d2l-en', 0.505675733089447, 'study', 4), ('uber/fiber', 0.505595326423645, 'data', 1), ('firmai/industry-machine-learning', 0.5053890347480774, 'study', 1), ('jina-ai/jina', 0.5048282146453857, 'ml', 4), ('deepmind/dm-haiku', 0.5038338303565979, 'ml-dl', 2), ('huggingface/huggingface_hub', 0.5031947493553162, 'ml', 3), ('deepmind/dm_control', 0.502716064453125, 'ml-rl', 3)]

97

3

null

14.02

360

260

48

0

5

4

5

359

210

90

0.6

55

1,710

perf

https://github.com/facebookincubator/cinder

['cpython']

null

[]

null

facebookincubator/cinder

cinder

3,301

121

60

Python

https://trycinder.com

Cinder is Meta's internal performance-oriented production version of CPython.

facebookincubator

2024-01-14

2021-03-16

150

22.006667

https://avatars.githubusercontent.com/u/19538647?v=4

Cinder is Meta's internal performance-oriented production version of CPython.

['compiler', 'interpreter', 'jit', 'runtime']

['compiler', 'cpython', 'interpreter', 'jit', 'runtime']

2024-01-13

[('rustpython/rustpython', 0.5831960439682007, 'util', 3), ('python/cpython', 0.5806695222854614, 'util', 1), ('faster-cpython/ideas', 0.5721518397331238, 'perf', 1), ('faster-cpython/tools', 0.5622638463973999, 'perf', 1), ('pypy/pypy', 0.5570579767227173, 'util', 2), ('brandtbucher/specialist', 0.5538285374641418, 'perf', 1), ('cython/cython', 0.5495518445968628, 'util', 1), ('scikit-build/scikit-build', 0.5411034226417542, 'ml', 1), ('fastai/fastcore', 0.5330604910850525, 'util', 0), ('sumerc/yappi', 0.5309968590736389, 'profiling', 0), ('astral-sh/ruff', 0.5143499374389648, 'util', 0), ('p403n1x87/austin', 0.5041605830192566, 'profiling', 0)]

1,760

6

null

7.19

10

8

34

0

12

14

90

1.2

55

1,293

llm

https://github.com/microsoft/lmops

[]

null

[]

null

microsoft/lmops

LMOps

2,828

192

55

Python

https://aka.ms/GeneralAI

General technology for enabling AI capabilities w/ LLMs and MLLMs

microsoft

2024-01-13

2022-12-13

59

47.932203

https://avatars.githubusercontent.com/u/6154722?v=4

General technology for enabling AI capabilities w/ LLMs and MLLMs

['agi', 'gpt', 'language-model', 'llm', 'lm', 'lmops', 'nlp', 'pretraining', 'prompt', 'promptist', 'x-prompt']

2024-01-02

[('mlc-ai/mlc-llm', 0.7063540816307068, 'llm', 2), ('microsoft/promptflow', 0.6579537987709045, 'llm', 3), ('prefecthq/marvin', 0.6434080600738525, 'nlp', 2), ('lastmile-ai/aiconfig', 0.6332518458366394, 'util', 1), ('bentoml/bentoml', 0.6321725249290466, 'ml-ops', 1), ('cheshire-cat-ai/core', 0.6224048137664795, 'llm', 1), ('operand/agency', 0.6131894588470459, 'llm', 2), ('microsoft/generative-ai-for-beginners', 0.6037994623184204, 'study', 2), ('pathwaycom/llm-app', 0.6022082567214966, 'llm', 1), ('microsoft/semantic-kernel', 0.6015781760215759, 'llm', 1), ('arize-ai/phoenix', 0.5890821814537048, 'ml-interpretability', 0), ('pytorchlightning/pytorch-lightning', 0.5851262211799622, 'ml-dl', 0), ('antonosika/gpt-engineer', 0.5837531089782715, 'llm', 0), ('microsoft/torchscale', 0.5832264423370361, 'llm', 0), ('bentoml/openllm', 0.581097424030304, 'ml-ops', 1), ('nebuly-ai/nebullvm', 0.5789636373519897, 'perf', 1), ('mindsdb/mindsdb', 0.5788654088973999, 'data', 2), ('lucidrains/toolformer-pytorch', 0.5752981901168823, 'llm', 1), ('torantulino/auto-gpt', 0.5733479261398315, 'llm', 0), ('ludwig-ai/ludwig', 0.5721259713172913, 'ml-ops', 1), ('argilla-io/argilla', 0.5673712491989136, 'nlp', 2), ('oneil512/insight', 0.5636782050132751, 'ml', 2), ('transformeroptimus/superagi', 0.5605264902114868, 'llm', 2), ('deepset-ai/haystack', 0.5590223073959351, 'llm', 2), ('agenta-ai/agenta', 0.5574962496757507, 'llm', 1), ('llmware-ai/llmware', 0.5573378205299377, 'llm', 1), ('microsoft/autogen', 0.555975079536438, 'llm', 1), ('sweepai/sweep', 0.5525568127632141, 'llm', 1), ('tigerlab-ai/tiger', 0.5503789186477661, 'llm', 1), ('microsoft/promptcraft-robotics', 0.5502687096595764, 'sim', 1), ('giskard-ai/giskard', 0.5501245260238647, 'data', 0), ('hegelai/prompttools', 0.5492219924926758, 'llm', 0), ('explosion/spacy-llm', 0.5478001832962036, 'llm', 2), ('promptslab/awesome-prompt-engineering', 0.538474440574646, 'study', 2), ('nccr-itmo/fedot', 0.5380227565765381, 'ml-ops', 0), ('hpcaitech/colossalai', 0.5340853929519653, 'llm', 0), ('mlflow/mlflow', 0.5320460200309753, 'ml-ops', 0), ('microsoft/jarvis', 0.5317671895027161, 'llm', 0), ('rasahq/rasa', 0.5303319096565247, 'llm', 1), ('chatarena/chatarena', 0.529494047164917, 'llm', 0), ('avaiga/taipy', 0.5267688632011414, 'data', 0), ('thilinarajapakse/simpletransformers', 0.5261474251747131, 'nlp', 0), ('young-geng/easylm', 0.5255038738250732, 'llm', 1), ('embedchain/embedchain', 0.5240100622177124, 'llm', 1), ('bigscience-workshop/petals', 0.5237755179405212, 'data', 2), ('googlecloudplatform/vertex-ai-samples', 0.5236150026321411, 'ml', 0), ('rcgai/simplyretrieve', 0.5208574533462524, 'llm', 1), ('nomic-ai/gpt4all', 0.5191216468811035, 'llm', 1), ('google/dopamine', 0.5175570249557495, 'ml-rl', 0), ('polyaxon/polyaxon', 0.5171562433242798, 'ml-ops', 0), ('guardrails-ai/guardrails', 0.5142502784729004, 'llm', 1), ('onnx/onnx', 0.5136048793792725, 'ml', 0), ('eugeneyan/obsidian-copilot', 0.5132716298103333, 'llm', 1), ('unity-technologies/ml-agents', 0.5131751298904419, 'ml-rl', 0), ('vllm-project/vllm', 0.5128405094146729, 'llm', 2), ('huggingface/datasets', 0.5126212239265442, 'nlp', 1), ('nvidia/nemo', 0.5125614404678345, 'nlp', 2), ('h2oai/h2o-llmstudio', 0.5096468329429626, 'llm', 2), ('jina-ai/thinkgpt', 0.5094317197799683, 'llm', 1), ('ml-tooling/opyrator', 0.5080411434173584, 'viz', 0), ('microsoft/unilm', 0.5072470903396606, 'nlp', 2), ('activeloopai/deeplake', 0.504906177520752, 'ml-ops', 1), ('pan-ml/panml', 0.5039084553718567, 'llm', 0), ('intel/intel-extension-for-transformers', 0.5034509301185608, 'perf', 0), ('titanml/takeoff', 0.5029642581939697, 'llm', 2), ('ray-project/ray', 0.5007473826408386, 'ml-ops', 0)]

22

4

null

1.54

68

54

13

0

68

95

90

1.4

55

51

testing

https://github.com/nedbat/coveragepy

[]

null

[]

null

nedbat/coveragepy

coveragepy

2,742

392

32

Python

https://coverage.readthedocs.io

The code coverage tool for Python

nedbat

2024-01-12

2018-06-23

292

9.376649

null

The code coverage tool for Python

[]

2024-01-13

[('eugeneyan/python-collab-template', 0.6858402490615845, 'template', 0), ('wolever/parameterized', 0.6841293573379517, 'testing', 0), ('pytest-dev/pytest-bdd', 0.6206257939338684, 'testing', 0), ('ionelmc/pytest-benchmark', 0.6183704733848572, 'testing', 0), ('eleutherai/pyfra', 0.6178824305534363, 'ml', 0), ('pmorissette/bt', 0.6093915700912476, 'finance', 0), ('landscapeio/prospector', 0.6040084362030029, 'util', 0), ('rubik/radon', 0.6033869981765747, 'util', 0), ('alexmojaki/snoop', 0.6032272577285767, 'debug', 0), ('pytest-dev/pytest-cov', 0.5966586470603943, 'testing', 0), ('pympler/pympler', 0.5953695178031921, 'perf', 0), ('sourcery-ai/sourcery', 0.5949026942253113, 'util', 0), ('getsentry/responses', 0.5841493606567383, 'testing', 0), ('pyutils/line_profiler', 0.5808612108230591, 'profiling', 0), ('buildbot/buildbot', 0.57981938123703, 'util', 0), ('google/pytype', 0.5753951072692871, 'typing', 0), ('klen/pylama', 0.5741574764251709, 'util', 0), ('pycqa/pyflakes', 0.5710163116455078, 'util', 0), ('gaogaotiantian/viztracer', 0.5709172487258911, 'profiling', 0), ('pythonprofilers/memory_profiler', 0.5676537156105042, 'profiling', 0), ('facebook/pyre-check', 0.5666431784629822, 'typing', 0), ('pytoolz/toolz', 0.5574312210083008, 'util', 0), ('samuelcolvin/python-devtools', 0.5552131533622742, 'debug', 0), ('hhatto/autopep8', 0.5550077557563782, 'util', 0), ('pypy/pypy', 0.5531808733940125, 'util', 0), ('grantjenks/blue', 0.5528746843338013, 'util', 0), ('dosisod/refurb', 0.5513451099395752, 'util', 0), ('reloadware/reloadium', 0.5490651726722717, 'profiling', 0), ('psf/black', 0.5479041337966919, 'util', 0), ('python/cpython', 0.5459318161010742, 'util', 0), ('taverntesting/tavern', 0.5402073264122009, 'testing', 0), ('snyk/faker-security', 0.5369202494621277, 'security', 0), ('samuelcolvin/dirty-equals', 0.5362508296966553, 'util', 0), ('google/yapf', 0.535642147064209, 'util', 0), ('spulec/freezegun', 0.5298979878425598, 'testing', 0), ('lk-geimfari/mimesis', 0.5268024206161499, 'data', 0), ('aswinnnn/pyscan', 0.525583028793335, 'security', 0), ('jendrikseipp/vulture', 0.5239750146865845, 'util', 0), ('mgedmin/check-manifest', 0.5218181610107422, 'util', 0), ('fchollet/deep-learning-with-python-notebooks', 0.521513819694519, 'study', 0), ('locustio/locust', 0.5198348760604858, 'testing', 0), ('astral-sh/ruff', 0.5197017788887024, 'util', 0), ('agronholm/typeguard', 0.5188262462615967, 'typing', 0), ('amaargiru/pyroad', 0.5170186161994934, 'study', 0), ('requests/toolbelt', 0.5164726376533508, 'util', 0), ('klen/py-frameworks-bench', 0.514492928981781, 'perf', 0), ('microsoft/playwright-python', 0.5143460631370544, 'testing', 0), ('pycqa/bandit', 0.5142317414283752, 'security', 0), ('pyston/pyston', 0.5141503810882568, 'util', 0), ('jiffyclub/snakeviz', 0.5139472484588623, 'profiling', 0), ('cuemacro/finmarketpy', 0.5129390954971313, 'finance', 0), ('cobrateam/splinter', 0.512545645236969, 'testing', 0), ('hypothesisworks/hypothesis', 0.5107763409614563, 'testing', 0), ('pytest-dev/pytest-xdist', 0.5098601579666138, 'testing', 0), ('benfred/py-spy', 0.5097211599349976, 'profiling', 0), ('featurelabs/featuretools', 0.5096982717514038, 'ml', 0), ('brandon-rhodes/python-patterns', 0.5084773302078247, 'util', 0), ('microsoft/pycodegpt', 0.506847083568573, 'llm', 0), ('samuelcolvin/pytest-pretty', 0.506611704826355, 'testing', 0), ('hadialqattan/pycln', 0.5058234930038452, 'util', 0), ('pycaret/pycaret', 0.5046213269233704, 'ml', 0), ('google/python-fire', 0.5045384764671326, 'term', 0), ('pycqa/flake8', 0.5013235807418823, 'util', 0), ('google/latexify_py', 0.5010238885879517, 'util', 0)]

168

6

null

8.23

55

30

68

0

15

23

15

55

138

90

2.5

55

1,281

viz

https://github.com/pyvista/pyvista

[]

null

[]

null

pyvista/pyvista

pyvista

2,144

407

34

Python

https://docs.pyvista.org

3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK)

pyvista

2024-01-14

2017-05-31

347

6.16345

https://avatars.githubusercontent.com/u/50384771?v=4

3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK)

['3d', 'mesh', 'mesh-processing', 'meshviewer', 'open-science', 'plotting', 'scientific-research', 'scientific-visualization', 'visualization', 'vtk']

2024-01-13

[('marcomusy/vedo', 0.7296451330184937, 'viz', 6), ('pyqtgraph/pyqtgraph', 0.6187593936920166, 'viz', 2), ('contextlab/hypertools', 0.5857540369033813, 'ml', 1), ('enthought/mayavi', 0.5794352293014526, 'viz', 2), ('districtdatalabs/yellowbrick', 0.578895092010498, 'ml', 1), ('holoviz/hvplot', 0.5786033868789673, 'pandas', 1), ('holoviz/holoviz', 0.5743590593338013, 'viz', 0), ('mckinsey/vizro', 0.5597613453865051, 'viz', 1), ('bokeh/bokeh', 0.559531569480896, 'viz', 2), ('isl-org/open3d', 0.5594555735588074, 'sim', 3), ('matplotlib/matplotlib', 0.5509993433952332, 'viz', 1), ('man-group/dtale', 0.5372913479804993, 'viz', 1), ('plotly/plotly.py', 0.5286508798599243, 'viz', 1), ('visgl/deck.gl', 0.5255587100982666, 'viz', 1), ('residentmario/geoplot', 0.5253320336341858, 'gis', 0), ('holoviz/panel', 0.5228663682937622, 'viz', 0), ('gaogaotiantian/viztracer', 0.5193122029304504, 'profiling', 1), ('polyaxon/datatile', 0.5150445699691772, 'pandas', 0), ('maartenbreddels/ipyvolume', 0.5043342709541321, 'jupyter', 2), ('pygraphviz/pygraphviz', 0.5015963315963745, 'viz', 0)]

153

4

null

15.13

391

278

81

0

12

19

12

390

1,158

90

3

55

371

gis

https://github.com/microsoft/torchgeo

[]

null

[]

null

microsoft/torchgeo

torchgeo

2,046

247

45

Python

https://torchgeo.rtfd.io

TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data

microsoft

2024-01-12

2021-05-21

140

14.554878

https://avatars.githubusercontent.com/u/6154722?v=4

TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data

['computer-vision', 'datasets', 'deep-learning', 'earth-observation', 'geospatial', 'models', 'pytorch', 'remote-sensing', 'satellite-imagery', 'torchvision', 'transforms']

2024-01-12

[('datasystemslab/geotorch', 0.6509654521942139, 'gis', 1), ('developmentseed/label-maker', 0.629837691783905, 'gis', 4), ('remotesensinglab/raster4ml', 0.6221429705619812, 'gis', 1), ('azavea/raster-vision', 0.6176372766494751, 'gis', 5), ('osgeo/grass', 0.6095272302627563, 'gis', 3), ('huggingface/datasets', 0.570610761642456, 'nlp', 4), ('nvlabs/gcvit', 0.5610058307647705, 'diffusion', 1), ('osgeo/gdal', 0.5599908828735352, 'gis', 1), ('fatiando/verde', 0.5598282217979431, 'gis', 1), ('opengeos/earthformer', 0.5563389658927917, 'gis', 2), ('aleju/imgaug', 0.5551947355270386, 'ml', 1), ('plant99/felicette', 0.554535448551178, 'gis', 3), ('kornia/kornia', 0.5526466369628906, 'ml-dl', 3), ('roboflow/notebooks', 0.5472760200500488, 'study', 3), ('awslabs/autogluon', 0.5401058197021484, 'ml', 3), ('roboflow/supervision', 0.5378150939941406, 'ml', 3), ('opengeos/segment-geospatial', 0.5342783331871033, 'gis', 2), ('deci-ai/super-gradients', 0.5279808640480042, 'ml-dl', 3), ('rwightman/pytorch-image-models', 0.5265195965766907, 'ml-dl', 1), ('lutzroeder/netron', 0.5072435140609741, 'ml', 2)]

53

7

null

10.5

171

132

32

0

4

171

261

90

1.5

55

765

nlp

https://github.com/huggingface/setfit

[]

null

[]

null

huggingface/setfit

setfit

1,804

185

21

Jupyter Notebook

https://hf.co/docs/setfit

Efficient few-shot learning with Sentence Transformers

huggingface

2024-01-13

2022-06-30

82

21.810017

https://avatars.githubusercontent.com/u/25720743?v=4

Efficient few-shot learning with Sentence Transformers

['few-shot-learning', 'nlp', 'sentence-transformers']

2024-01-11

[('eleutherai/lm-evaluation-harness', 0.6814461350440979, 'llm', 0), ('alibaba/easynlp', 0.5513603091239929, 'nlp', 1), ('ofa-sys/ofa', 0.5320513844490051, 'llm', 0), ('bigscience-workshop/t-zero', 0.5152558088302612, 'llm', 0), ('google-research/electra', 0.5080073475837708, 'ml-dl', 1)]

48

4

null

4.63

110

86

19

0

5

9

5

110

182

90

1.7

55

1,572

llm

https://github.com/pathwaycom/llm-app

[]

null

[]

null

pathwaycom/llm-app

llm-app

1,568

101

21

Python

https://pathway.com/developers/showcases/llm-app-pathway/

LLM App is a production framework for building and serving AI applications and LLM-enabled real-time data pipelines.

pathwaycom

2024-01-13

2023-07-19

27

56.287179

https://avatars.githubusercontent.com/u/25750857?v=4

LLM App is a production framework for building and serving AI applications and LLM-enabled real-time data pipelines.

['chatbot', 'hugging-face', 'llm', 'llm-local', 'llm-prompting', 'llm-security', 'llmops', 'machine-learning', 'open-ai', 'pathway', 'rag', 'real-time', 'retrieval-augmented-generation', 'vector-database', 'vector-index']

2023-12-27

[('microsoft/semantic-kernel', 0.7631767988204956, 'llm', 1), ('microsoft/promptflow', 0.7594974040985107, 'llm', 1), ('deepset-ai/haystack', 0.7468881607055664, 'llm', 1), ('cheshire-cat-ai/core', 0.6957066059112549, 'llm', 2), ('deep-diver/llm-as-chatbot', 0.6957004070281982, 'llm', 1), ('embedchain/embedchain', 0.6783232688903809, 'llm', 1), ('intel/intel-extension-for-transformers', 0.6731693148612976, 'perf', 1), ('hwchase17/langchain', 0.6680853366851807, 'llm', 1), ('nebuly-ai/nebullvm', 0.6677808165550232, 'perf', 1), ('nomic-ai/gpt4all', 0.6673745512962341, 'llm', 1), ('lancedb/lancedb', 0.6573936343193054, 'data', 1), ('tigerlab-ai/tiger', 0.6506632566452026, 'llm', 2), ('h2oai/h2o-llmstudio', 0.6417025327682495, 'llm', 2), ('alphasecio/langchain-examples', 0.6350022554397583, 'llm', 1), ('bigscience-workshop/petals', 0.6320452690124512, 'data', 2), ('mnotgod96/appagent', 0.6296766400337219, 'llm', 1), ('shishirpatil/gorilla', 0.6179982423782349, 'llm', 1), ('mlc-ai/mlc-llm', 0.6101855039596558, 'llm', 1), ('activeloopai/deeplake', 0.6084655523300171, 'ml-ops', 3), ('microsoft/lmops', 0.6022082567214966, 'llm', 1), ('ludwig-ai/ludwig', 0.5985682010650635, 'ml-ops', 2), ('prefecthq/marvin', 0.5963694453239441, 'nlp', 1), ('superduperdb/superduperdb', 0.595395028591156, 'data', 2), ('alpha-vllm/llama2-accessory', 0.5948898196220398, 'llm', 0), ('bentoml/bentoml', 0.5931383371353149, 'ml-ops', 2), ('iryna-kondr/scikit-llm', 0.5918958187103271, 'llm', 2), ('lastmile-ai/aiconfig', 0.5902220606803894, 'util', 1), ('run-llama/rags', 0.5891484618186951, 'llm', 3), ('young-geng/easylm', 0.5865856409072876, 'llm', 1), ('rcgai/simplyretrieve', 0.5839216113090515, 'llm', 2), ('zilliztech/gptcache', 0.5837850570678711, 'llm', 2), ('chatarena/chatarena', 0.5828151702880859, 'llm', 0), ('microsoft/torchscale', 0.5825396180152893, 'llm', 1), ('argilla-io/argilla', 0.5815805792808533, 'nlp', 2), ('explosion/spacy-llm', 0.5805977582931519, 'llm', 2), ('jerryjliu/llama_index', 0.5804813504219055, 'llm', 3), ('microsoft/autogen', 0.5762929916381836, 'llm', 2), ('chainlit/chainlit', 0.5761844515800476, 'llm', 1), ('llmware-ai/llmware', 0.5754697322845459, 'llm', 3), ('berriai/litellm', 0.5751776695251465, 'llm', 2), ('ajndkr/lanarky', 0.5696076154708862, 'llm', 1), ('bentoml/openllm', 0.5679009556770325, 'ml-ops', 2), ('vllm-project/vllm', 0.5676781535148621, 'llm', 2), ('jina-ai/jina', 0.567528486251831, 'ml', 2), ('mindsdb/mindsdb', 0.5670859217643738, 'data', 3), ('rasahq/rasa', 0.5657259821891785, 'llm', 2), ('agenta-ai/agenta', 0.5643110275268555, 'llm', 3), ('microsoft/promptcraft-robotics', 0.5630580186843872, 'sim', 1), ('paddlepaddle/paddlenlp', 0.5630315542221069, 'llm', 1), ('avaiga/taipy', 0.5616130232810974, 'data', 0), ('mmabrouk/chatgpt-wrapper', 0.5610566735267639, 'llm', 2), ('skypilot-org/skypilot', 0.554336428642273, 'llm', 1), ('confident-ai/deepeval', 0.549860417842865, 'testing', 2), ('citadel-ai/langcheck', 0.5472109317779541, 'llm', 0), ('microsoft/jarvis', 0.544485330581665, 'llm', 0), ('operand/agency', 0.5409510135650635, 'llm', 3), ('minimaxir/simpleaichat', 0.5408278703689575, 'llm', 0), ('hegelai/prompttools', 0.5340642333030701, 'llm', 1), ('run-llama/llama-hub', 0.5336598753929138, 'data', 1), ('gunthercox/chatterbot', 0.5325236916542053, 'nlp', 2), ('mlc-ai/web-llm', 0.5320335030555725, 'llm', 1), ('sweepai/sweep', 0.5312567353248596, 'llm', 1), ('night-chen/toolqa', 0.5218302607536316, 'llm', 0), ('bobazooba/xllm', 0.5216497778892517, 'llm', 1), ('eugeneyan/open-llms', 0.5204359889030457, 'study', 1), ('lm-sys/fastchat', 0.5164425373077393, 'llm', 1), ('streamlit/streamlit', 0.5164030194282532, 'viz', 1), ('googlecloudplatform/vertex-ai-samples', 0.5163154006004333, 'ml', 0), ('gradio-app/gradio', 0.5149146914482117, 'viz', 1), ('ml-tooling/opyrator', 0.5144424438476562, 'viz', 1), ('larsbaunwall/bricky', 0.5143710374832153, 'llm', 0), ('salesforce/xgen', 0.5143515467643738, 'llm', 1), ('titanml/takeoff', 0.5129966735839844, 'llm', 1), ('langchain-ai/langgraph', 0.5122884511947632, 'llm', 0), ('microsoft/generative-ai-for-beginners', 0.5098125338554382, 'study', 0), ('deeppavlov/deeppavlov', 0.5093848705291748, 'nlp', 2), ('thudm/chatglm2-6b', 0.5088384747505188, 'llm', 1), ('pathwaycom/pathway', 0.5075528621673584, 'data', 3), ('aimhubio/aim', 0.506819486618042, 'ml-ops', 1), ('togethercomputer/openchatkit', 0.5052575469017029, 'nlp', 1), ('zenml-io/zenml', 0.504523515701294, 'ml-ops', 3), ('deep-diver/pingpong', 0.5041395425796509, 'llm', 0), ('lucidrains/toolformer-pytorch', 0.5037291049957275, 'llm', 0)]

15

5

null

2.19

7

4

6

1

8

16

8

7

6

90

0.9

55

1,767

ml-ops

https://github.com/meltano/meltano

[]

null

[]

null

meltano/meltano

meltano

1,447

139

13

Python

https://meltano.com/

Meltano: the declarative code-first data integration engine that powers your wildest data and ML-powered product ideas. Say goodbye to writing, maintaining, and scaling your own API integrations.

meltano

2024-01-14

2021-06-21

136

10.628541

https://avatars.githubusercontent.com/u/43816713?v=4

Meltano: the declarative code-first data integration engine that powers your wildest data and ML-powered product ideas. Say goodbye to writing, maintaining, and scaling your own API integrations.

['connectors', 'data', 'data-engineering', 'data-pipelines', 'dataops', 'dataops-platform', 'elt', 'extract-data', 'integration', 'loaders', 'meltano', 'meltano-sdk', 'open-source', 'opensource', 'pipelines', 'singer', 'tap', 'taps', 'target', 'targets']

2024-01-12

[('mage-ai/mage-ai', 0.6557142734527588, 'ml-ops', 5), ('airbytehq/airbyte', 0.6305922865867615, 'data', 3), ('ploomber/ploomber', 0.6284797787666321, 'ml-ops', 2), ('orchest/orchest', 0.6131107211112976, 'ml-ops', 2), ('simonw/datasette', 0.6087267398834229, 'data', 0), ('avaiga/taipy', 0.608718752861023, 'data', 2), ('dagster-io/dagster', 0.60458904504776, 'ml-ops', 2), ('linealabs/lineapy', 0.5844327211380005, 'jupyter', 0), ('flyteorg/flyte', 0.5828467607498169, 'ml-ops', 2), ('kestra-io/kestra', 0.5790954232215881, 'ml-ops', 3), ('dagworks-inc/hamilton', 0.5787143111228943, 'ml-ops', 1), ('streamlit/streamlit', 0.5685817003250122, 'viz', 0), ('polyaxon/datatile', 0.5661336183547974, 'pandas', 1), ('netflix/metaflow', 0.5626580119132996, 'ml-ops', 0), ('airbnb/omniduct', 0.5620505213737488, 'data', 0), ('whylabs/whylogs', 0.5477058291435242, 'util', 1), ('hi-primus/optimus', 0.5476229190826416, 'ml-ops', 0), ('kedro-org/kedro', 0.5286129117012024, 'ml-ops', 0), ('fugue-project/fugue', 0.5231815576553345, 'pandas', 0), ('zenml-io/zenml', 0.5218309760093689, 'ml-ops', 1), ('featureform/embeddinghub', 0.5155656337738037, 'nlp', 0), ('polyaxon/polyaxon', 0.5144167542457581, 'ml-ops', 1), ('ml-tooling/opyrator', 0.5139985084533691, 'viz', 0), ('tiangolo/fastapi', 0.5132185220718384, 'web', 0), ('huggingface/datasets', 0.5098901391029358, 'nlp', 0), ('astronomer/astro-sdk', 0.5098263621330261, 'ml-ops', 1), ('drivendata/cookiecutter-data-science', 0.5092251300811768, 'template', 0), ('pythagora-io/gpt-pilot', 0.5066982507705688, 'llm', 0), ('merantix-momentum/squirrel-core', 0.506161093711853, 'ml', 1), ('great-expectations/great_expectations', 0.5034080147743225, 'ml-ops', 1), ('kubeflow/fairing', 0.5027660131454468, 'ml-ops', 0)]

157

4

null

20.71

143

110

31

0

19

106

19

143

296

90

2.1

55