Jordan Legg's picture

Jordan Legg PRO

takarajordan

AI & ML interests

Chief AI Officer @takara.ai. Diffusion, Inference optimisation and all things MultiModal.

Recent Activity

updated a Space 3 days ago
open-acc/README
new activity 3 days ago
open-acc/README:Update README.md
liked a dataset 3 days ago
takarajordan/LastFM_120K
View all activity

Organizations

Social Post Explorers's profile picture C4AI Community's profile picture takara.ai's profile picture Hugging Face Discord Community's profile picture Intelligent Estate's profile picture open/ acc's profile picture Donut Earthers ๐Ÿฉ's profile picture

takarajordan's activity

replied to s3nh's post 6 days ago
reacted to s3nh's post with โค๏ธ 6 days ago
view post
Post
1605
Welcome back,

Small Language Models Enthusiasts and GPU Poor oss enjoyers lets connect.
Just created an organization which main target is to have fun with smaller models tuneable on consumer range GPUs, feel free to join and lets have some fun, much love ;3

https://huggingface.co/SmolTuners
ยท
replied to merve's post 6 days ago
reacted to merve's post with ๐Ÿš€ 6 days ago
view post
Post
2319
Aya by Cohere For AI can now see! ๐Ÿ‘€

C4AI community has built Maya 8B, a new open-source multilingual VLM built on SigLIP and Aya 8B ๐ŸŒฑ works on 8 languages! ๐Ÿ—ฃ๏ธ

The authors extend Llava dataset using Aya's translation capabilities with 558k examples!
ry it here kkr5155/maya_demo

Dataset maya-multimodal/pretrain

Model maya-multimodal/maya ๐Ÿ‘
kudos @nahidalam and team
  • 1 reply
ยท
reacted to merve's post with ๐Ÿš€ 6 days ago
view post
Post
2902
Apollo is a new family of open-source video language models by Meta, where 3B model outperforms most 7B models and 7B outperforms most 30B models ๐Ÿงถ

โœจ the models come in 1.5B https://huggingface.co/Apollo-LMMs/Apollo-1_5B-t32, 3B https://huggingface.co/Apollo-LMMs/Apollo-3B-t32 and 7B https://huggingface.co/Apollo-LMMs/Apollo-7B-t32 with A2.0 license, based on Qwen1.5 & Qwen2
โœจ the authors also release a benchmark dataset https://huggingface.co/spaces/Apollo-LMMs/ApolloBench

The paper has a lot of experiments (they trained 84 models!) about what makes the video LMs work โฏ๏ธ

Try the demo for best setup here https://huggingface.co/spaces/Apollo-LMMs/Apollo-3B
they evaluate sampling strategies, scaling laws for models and datasets, video representation and more!
> The authors find out that whatever design decision was applied to small models also scale properly when the model and dataset are scaled ๐Ÿ“ˆ scaling dataset has diminishing returns for smaller models
> They evaluate frame sampling strategies, and find that FPS sampling is better than uniform sampling, and they find 8-32 tokens per frame optimal
> They also compare image encoders, they try a variation of models from shape optimized SigLIP to DINOv2
they find google/siglip-so400m-patch14-384 to be most powerful ๐Ÿ”ฅ
> they also compare freezing different parts of models, training all stages with some frozen parts give the best yield

They eventually release three models, where Apollo-3B outperforms most 7B models and Apollo 7B outperforms 30B models ๐Ÿ”ฅ
  • 3 replies
ยท
replied to sayakpaul's post 7 days ago
reacted to sayakpaul's post with ๐Ÿš€ 7 days ago
view post
Post
1547
In the past seven days, the Diffusers team has shipped:

1. Two new video models
2. One new image model
3. Two new quantization backends
4. Three new fine-tuning scripts
5. Multiple fixes and library QoL improvements

Coffee on me if someone can guess 1 - 4 correctly.
  • 1 reply
ยท
reacted to lorraine2's post with ๐Ÿš€ 7 days ago
view post
Post
1966
๐Ÿฆ™New NVIDIA paper: LLaMA-Mesh ๐Ÿฆ™

We enable large language models to generate and understand 3D meshes by representing them as text and fine-tuning. This unifies the 3D and text modalities in a single model and preserves language abilities, unlocking conversational 3D creation with mesh understanding.

๐Ÿ”Ž Project Page: https://research.nvidia.com/labs/toronto-ai/LLaMA-Mesh/
๐Ÿ•น๏ธ Interactive Demo: Zhengyi/LLaMA-Mesh (courtesy of HuggingFace and Gradio)
๐Ÿ“– Full Paper: https://arxiv.org/abs/2411.09595
๐Ÿ‘จโ€๐Ÿ’ปCode: https://github.com/nv-tlabs/LLaMa-Mesh
๐Ÿ’พ Model Checkpoint: Zhengyi/LLaMA-Mesh
๐Ÿงฉ Blender Addon: https://github.com/huggingface/meshgen (courtesy of Dylan Ebert)
๐ŸŽฅ 5-min Overview Video: https://youtu.be/eZNazN-1lPo?si=-idQa5aaceVw0Bbj (courtesy of AI Papers Academy)
reacted to DualityAI-RebekahBogdanoff's post with โค๏ธ๐Ÿ”ฅ 7 days ago
view post
Post
1932
Training YOLO with Synthetic Data from Duality AI's Falcon Simulation Software ๐ŸŽฎ๐Ÿ“Š
Hello again! ๐Ÿ‘‹ Duality.ai has released a second Google Colab and tutorial for training a YOLOv8 model using synthetic data from our Falcon simulation software!

https://falcon.duality.ai/secure/documentation/see-synth-work-no-specs?sidebarMode=learn#download-the-colab-notebook

Train using synthetic images of a soup can twin this time, and see it work on real-world images. ๐Ÿฅซ๐Ÿœ
The tutorial also walks you through how to add your own twin from our FalconCloud library, and our goal is to equip people like you to be able to create your own data for your own projects.

You'll have to create a free account to access the files, but once you do, you'll have access to not only this colab file, but also all of our lessons and our digital twin library. ๐ŸŽ“

Instructions for creating the synthetic data accessed by the colab notebook can be found here: https://falcon.duality.ai/secure/documentation/ex2-objdetection-newtwin?sidebarMode=learn

This method is a game-changer for cost-effective, scalable, and customizable datasets in computer vision.

Why Synthetic Data?๐Ÿค”
- Precise Annotations: Get bounding boxes, segmentation masks, and more without manual effort.
- Customizable Scenarios: Get comprehensive data and cover all corner cases by simulating diverse conditions like lighting, weather, visual occlusions, and more.

Whatโ€™s in the Notebook?๐Ÿ““
- Training & Evaluation: Train YOLOv8 with synthetic data and test its performance on real-world samples.

Letโ€™s Discuss!๐Ÿ’ฌ
Check out our discord to see how people are using the Falcon simulation software to develop strong datasets and train robust models. https://discord.com/invite/dualityfalconcommunity
  • 2 replies
ยท
reacted to prithivMLmods's post with โค๏ธ 7 days ago
view post
Post
3167
๐ŸŽ„ Here Before - Xmas๐ŸŽ…โœจ

๐Ÿง‘๐Ÿปโ€๐ŸŽ„Models
+ [ Xmas 2D Illustration ] : strangerzonehf/Flux-Xmas-Illustration-LoRA
+ [ Xmas 3D Art ] : strangerzonehf/Flux-Xmas-3D-LoRA
+ [ Xmas Chocolate ] : strangerzonehf/Flux-Xmas-Chocolate-LoRA
+ [ Xmas Isometric Kit ] : strangerzonehf/Flux-Xmas-Isometric-Kit-LoRA
+ [ Xmas Realpix ] : strangerzonehf/Flux-Xmas-Realpix-LoRA
+ [ Xmas Anime ] : strangerzonehf/Flux-Anime-Xmas-LoRA

โ„๏ธCollections
+ [ Xmas Art ] : strangerzonehf/christmas-pack-6758b199487adafaddb68f82
+ [ Stranger Zone Collection ] : prithivMLmods/stranger-zone-collections-org-6737118adcf2cb40d66d0c7e

๐ŸฅถPage
+ [ Stranger Zone ] : https://huggingface.co/strangerzonehf


.
.
.
@prithivMLmods ๐Ÿค—
reacted to davidberenstein1957's post with ๐Ÿ”ฅ 7 days ago
view post
Post
4105
Introducing the Synthetic Data Generator, a user-friendly application that takes a no-code approach to creating custom datasets with Large Language Models (LLMs). The best part: A simple step-by-step process, making dataset creation a non-technical breeze, allowing anyone to create datasets and models in minutes and without any code.

Blog: https://huggingface.co/blog/synthetic-data-generator
Space: argilla/synthetic-data-generator
ยท
reacted to cutechicken's post with โค๏ธ 7 days ago
view post
Post
2822
๐Ÿš€ RAGOndevice: High-Performance Local AI Document Analysis Assistant
๐Ÿ’ซ Core Value
RAGOndevice is a high-performance AI system running locally without cloud dependency. Using CohereForAI's optimized 7B model, it enables professional-grade document analysis on standard PCs. โœจ
๐ŸŒŸ Ondevice AI Advantages
1. ๐Ÿ”‹ Efficient Resource Utilization

๐ŸŽฏ Optimized 7B Model: Runs on standard PCs
โšก Local Processing: Instant response without cloud
๐Ÿ’ป Low-Spec Compatible: Performs well on regular GPUs
๐Ÿ”„ Optimized Memory: Ensures stable operation

2. ๐Ÿ›ก๏ธ Data Security & Cost Efficiency

๐Ÿ”’ Complete Privacy: No external data transmission
๐ŸŒ Offline Operation: No internet required
๐Ÿ’ฐ No Subscription: One-time installation
โš™๏ธ Resource Optimization: Uses existing hardware

๐ŸŽฎ Key Features
1. ๐Ÿ“Š Powerful Document Analysis

๐Ÿ“ Multi-Format Support: TXT, CSV, PDF, Parquet
๐Ÿง  Intelligent Analysis: Automatic structure recognition
๐Ÿ‘๏ธ OCR Support: Advanced PDF text extraction
๐Ÿ’ฌ Real-time Chat: Natural language interaction

2. ๐Ÿ” Local RAG System

๐ŸŽฏ Efficient Search: TF-IDF based local search
๐Ÿงฉ Context Understanding: Accurate information retrieval
๐Ÿ“š Wikipedia Integration: Rich background knowledge

๐ŸŽฏ Use Cases

๐Ÿข Enterprise: Secure confidential document processing
๐Ÿ”ฌ Personal Research: Private data analysis
๐Ÿ“š Education: Personal learning material analysis
๐Ÿ’ป Development: Local codebase analysis

โญ Differentiators

๐Ÿƒโ€โ™‚๏ธ Independent Operation: Zero cloud dependency
โšก Instant Response: No network latency
๐Ÿ” Complete Security: Full data control
๐Ÿ’Ž Cost Efficiency: No ongoing costs

๐Ÿ”ฎ Future Plans

๐Ÿš€ Enhanced model optimization
๐Ÿ“š Local knowledge base expansion
โšก Hardware optimization
๐Ÿ“ Extended file support


๐ŸŒŸ RAGOndevice democratizes high-performance AI, providing the optimal local AI solution for security-sensitive environments. ๐Ÿš€

๐Ÿ”ฅ Power of Local AI: Experience enterprise-grade AI capabilities right on your device!

VIDraft/RAGOndevice
reacted to lewtun's post with ๐Ÿ”ฅ๐Ÿš€ 7 days ago
view post
Post
6427
We outperform Llama 70B with Llama 3B on hard math by scaling test-time compute ๐Ÿ”ฅ

How? By combining step-wise reward models with tree search algorithms :)

We show that smol models can match or exceed the performance of their much larger siblings when given enough "time to think"

We're open sourcing the full recipe and sharing a detailed blog post.

In our blog post we cover:

๐Ÿ“ˆ Compute-optimal scaling: How we implemented DeepMind's recipe to boost the mathematical capabilities of open models at test-time.

๐ŸŽ„ Diverse Verifier Tree Search (DVTS): An unpublished extension we developed to the verifier-guided tree search technique. This simple yet effective method improves diversity and delivers better performance, particularly at large test-time compute budgets.

๐Ÿงญ Search and Learn: A lightweight toolkit for implementing search strategies with LLMs and built for speed with vLLM

Here's the links:

- Blog post: HuggingFaceH4/blogpost-scaling-test-time-compute

- Code: https://github.com/huggingface/search-and-learn

Enjoy!
  • 2 replies
ยท
reacted to their post with ๐Ÿš€ 7 days ago
view post
Post
1045
I made an RSS feed for HuggingFace Daily Papers!! ๐Ÿค—

Just Subscribe here: https://papers.takara.ai/api/feed

It updates every 24 hours, completely written as a serverless go script with a Redis cache (to avoid hitting HF all the time).

I'm open sourcing the code, you can check out my repo and deploy it on Vercel extremely easily!
https://github.com/404missinglink/HF-Daily-Papers-Feeds

thanks to @John6666 @p3nGu1nZz for your early support
replied to their post 7 days ago
replied to their post 7 days ago
view reply

I preprocessed this into ChatML format to train the model takarajordan/WorldScenario-3.2B_GGUF and I used Unsloth to finetune it!

If you want more help join the HuggingFace discord, I'm always in there.

reacted to prithivMLmods's post with ๐Ÿค— 7 days ago
view post
Post
3167
๐ŸŽ„ Here Before - Xmas๐ŸŽ…โœจ

๐Ÿง‘๐Ÿปโ€๐ŸŽ„Models
+ [ Xmas 2D Illustration ] : strangerzonehf/Flux-Xmas-Illustration-LoRA
+ [ Xmas 3D Art ] : strangerzonehf/Flux-Xmas-3D-LoRA
+ [ Xmas Chocolate ] : strangerzonehf/Flux-Xmas-Chocolate-LoRA
+ [ Xmas Isometric Kit ] : strangerzonehf/Flux-Xmas-Isometric-Kit-LoRA
+ [ Xmas Realpix ] : strangerzonehf/Flux-Xmas-Realpix-LoRA
+ [ Xmas Anime ] : strangerzonehf/Flux-Anime-Xmas-LoRA

โ„๏ธCollections
+ [ Xmas Art ] : strangerzonehf/christmas-pack-6758b199487adafaddb68f82
+ [ Stranger Zone Collection ] : prithivMLmods/stranger-zone-collections-org-6737118adcf2cb40d66d0c7e

๐ŸฅถPage
+ [ Stranger Zone ] : https://huggingface.co/strangerzonehf


.
.
.
@prithivMLmods ๐Ÿค—
reacted to freddyaboulton's post with ๐Ÿš€ 7 days ago