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--- |
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base_model: jondurbin/bagel-dpo-7b-v0.4 |
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datasets: |
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- ai2_arc |
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- allenai/ultrafeedback_binarized_cleaned |
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- argilla/distilabel-intel-orca-dpo-pairs |
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- jondurbin/airoboros-3.2 |
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- codeparrot/apps |
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- facebook/belebele |
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- bluemoon-fandom-1-1-rp-cleaned |
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- boolq |
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- camel-ai/biology |
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- camel-ai/chemistry |
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- camel-ai/math |
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- camel-ai/physics |
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- jondurbin/contextual-dpo-v0.1 |
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- jondurbin/gutenberg-dpo-v0.1 |
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- jondurbin/py-dpo-v0.1 |
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- jondurbin/truthy-dpo-v0.1 |
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- LDJnr/Capybara |
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- jondurbin/cinematika-v0.1 |
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- WizardLM/WizardLM_evol_instruct_70k |
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- glaiveai/glaive-function-calling-v2 |
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- jondurbin/gutenberg-dpo-v0.1 |
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- grimulkan/LimaRP-augmented |
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- lmsys/lmsys-chat-1m |
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- ParisNeo/lollms_aware_dataset |
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- TIGER-Lab/MathInstruct |
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- Muennighoff/natural-instructions |
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- openbookqa |
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- kingbri/PIPPA-shareGPT |
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- piqa |
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- Vezora/Tested-22k-Python-Alpaca |
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- ropes |
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- cakiki/rosetta-code |
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- Open-Orca/SlimOrca |
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- b-mc2/sql-create-context |
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- squad_v2 |
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- mattpscott/airoboros-summarization |
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- migtissera/Synthia-v1.3 |
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- unalignment/toxic-dpo-v0.2 |
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- WhiteRabbitNeo/WRN-Chapter-1 |
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- WhiteRabbitNeo/WRN-Chapter-2 |
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- winogrande |
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language: |
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- en |
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library_name: transformers |
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license: apache-2.0 |
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quantized_by: mradermacher |
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--- |
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## About |
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<!-- ### quantize_version: 2 --> |
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<!-- ### output_tensor_quantised: 1 --> |
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<!-- ### convert_type: hf --> |
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<!-- ### vocab_type: --> |
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<!-- ### tags: nicoboss --> |
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weighted/imatrix quants of https://huggingface.co/jondurbin/bagel-dpo-7b-v0.4 |
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<!-- provided-files --> |
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static quants are available at https://huggingface.co/mradermacher/bagel-dpo-7b-v0.4-GGUF |
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## Usage |
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If you are unsure how to use GGUF files, refer to one of [TheBloke's |
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READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for |
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more details, including on how to concatenate multi-part files. |
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## Provided Quants |
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(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) |
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| Link | Type | Size/GB | Notes | |
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|:-----|:-----|--------:|:------| |
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| [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 | |
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| [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 | |
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| [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 | | |
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| [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 | |
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Here is a handy graph by ikawrakow comparing some lower-quality quant |
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types (lower is better): |
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 |
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And here are Artefact2's thoughts on the matter: |
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https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 |
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## FAQ / Model Request |
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See https://huggingface.co/mradermacher/model_requests for some answers to |
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questions you might have and/or if you want some other model quantized. |
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## Thanks |
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I thank my company, [nethype GmbH](https://www.nethype.de/), for letting |
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me use its servers and providing upgrades to my workstation to enable |
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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. |
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<!-- end --> |
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