|
--- |
|
base_model: jondurbin/bagel-dpo-7b-v0.4 |
|
datasets: |
|
- ai2_arc |
|
- allenai/ultrafeedback_binarized_cleaned |
|
- argilla/distilabel-intel-orca-dpo-pairs |
|
- jondurbin/airoboros-3.2 |
|
- codeparrot/apps |
|
- facebook/belebele |
|
- bluemoon-fandom-1-1-rp-cleaned |
|
- boolq |
|
- camel-ai/biology |
|
- camel-ai/chemistry |
|
- camel-ai/math |
|
- camel-ai/physics |
|
- jondurbin/contextual-dpo-v0.1 |
|
- jondurbin/gutenberg-dpo-v0.1 |
|
- jondurbin/py-dpo-v0.1 |
|
- jondurbin/truthy-dpo-v0.1 |
|
- LDJnr/Capybara |
|
- jondurbin/cinematika-v0.1 |
|
- WizardLM/WizardLM_evol_instruct_70k |
|
- glaiveai/glaive-function-calling-v2 |
|
- jondurbin/gutenberg-dpo-v0.1 |
|
- grimulkan/LimaRP-augmented |
|
- lmsys/lmsys-chat-1m |
|
- ParisNeo/lollms_aware_dataset |
|
- TIGER-Lab/MathInstruct |
|
- Muennighoff/natural-instructions |
|
- openbookqa |
|
- kingbri/PIPPA-shareGPT |
|
- piqa |
|
- Vezora/Tested-22k-Python-Alpaca |
|
- ropes |
|
- cakiki/rosetta-code |
|
- Open-Orca/SlimOrca |
|
- b-mc2/sql-create-context |
|
- squad_v2 |
|
- mattpscott/airoboros-summarization |
|
- migtissera/Synthia-v1.3 |
|
- unalignment/toxic-dpo-v0.2 |
|
- WhiteRabbitNeo/WRN-Chapter-1 |
|
- WhiteRabbitNeo/WRN-Chapter-2 |
|
- winogrande |
|
language: |
|
- en |
|
library_name: transformers |
|
license: apache-2.0 |
|
quantized_by: mradermacher |
|
--- |
|
## About |
|
|
|
<!-- ### quantize_version: 2 --> |
|
<!-- ### output_tensor_quantised: 1 --> |
|
<!-- ### convert_type: hf --> |
|
<!-- ### vocab_type: --> |
|
<!-- ### tags: nicoboss --> |
|
weighted/imatrix quants of https://huggingface.co/jondurbin/bagel-dpo-7b-v0.4 |
|
|
|
<!-- provided-files --> |
|
static quants are available at https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-GGUF |
|
## Usage |
|
|
|
If you are unsure how to use GGUF files, refer to one of [TheBloke's |
|
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for |
|
more details, including on how to concatenate multi-part files. |
|
|
|
## Provided Quants |
|
|
|
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) |
|
|
|
| Link | Type | Size/GB | Notes | |
|
|:-----|:-----|--------:|:------| |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-IQ1_S.gguf) | i1-IQ1_S | 1.7 | for the desperate | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-IQ1_M.gguf) | i1-IQ1_M | 1.9 | mostly desperate | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.1 | | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.3 | | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-IQ2_S.gguf) | i1-IQ2_S | 2.4 | | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-IQ2_M.gguf) | i1-IQ2_M | 2.6 | | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-Q2_K.gguf) | i1-Q2_K | 2.8 | IQ3_XXS probably better | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 2.9 | lower quality | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.1 | | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.3 | IQ3_XS probably better | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-IQ3_S.gguf) | i1-IQ3_S | 3.3 | beats Q3_K* | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-IQ3_M.gguf) | i1-IQ3_M | 3.4 | | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-Q3_K_M.gguf) | i1-Q3_K_M | 3.6 | IQ3_S probably better | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-Q3_K_L.gguf) | i1-Q3_K_L | 3.9 | IQ3_M probably better | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.0 | | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-Q4_0_4_4.gguf) | i1-Q4_0_4_4 | 4.2 | fast on arm, low quality | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-Q4_0_4_8.gguf) | i1-Q4_0_4_8 | 4.2 | fast on arm+i8mm, low quality | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-Q4_0_8_8.gguf) | i1-Q4_0_8_8 | 4.2 | fast on arm+sve, low quality | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-Q4_0.gguf) | i1-Q4_0 | 4.2 | fast, low quality | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.2 | optimal size/speed/quality | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-Q4_K_M.gguf) | i1-Q4_K_M | 4.5 | fast, recommended | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.1 | | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-Q5_K_M.gguf) | i1-Q5_K_M | 5.2 | | |
|
| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-i1-GGUF/resolve/main/bagel-dpo-7b-v0.4.i1-Q6_K.gguf) | i1-Q6_K | 6.0 | practically like static Q6_K | |
|
|
|
Here is a handy graph by ikawrakow comparing some lower-quality quant |
|
types (lower is better): |
|
|
|
 |
|
|
|
And here are Artefact2's thoughts on the matter: |
|
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 |
|
|
|
## FAQ / Model Request |
|
|
|
See https://huggingface.co/mradermacher/model_requests for some answers to |
|
questions you might have and/or if you want some other model quantized. |
|
|
|
## Thanks |
|
|
|
I thank my company, [nethype GmbH](https://www.nethype.de/), for letting |
|
me use its servers and providing upgrades to my workstation to enable |
|
this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to. |
|
|
|
<!-- end --> |
|
|
