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--- |
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language: |
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- en |
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library_name: transformers |
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--- |
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Converted with https://github.com/qwopqwop200/GPTQ-for-LLaMa |
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All models tested on A100-80G |
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*Conversion may require lot of RAM, LLaMA-7b takes ~12 GB, 13b around 21 GB, 30b around 62 and 65b takes more than 120 GB of RAM. |
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Installation instructions as mentioned in above repo: |
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1. Install Anaconda and create a venv with python 3.8 |
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2. Install pytorch(tested with torch-1.13-cu116) |
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3. Install Transformers library (you'll need the latest transformers with this PR : https://github.com/huggingface/transformers/pull/21955 ). |
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4. Install sentencepiece from pip |
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5. Run python cuda_setup.py install in venv |
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6. You can either convert the llama models yourself with the instructions from GPTQ-for-llama repo |
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7. or directly use these weights by individually downloading them following these instructions (https://huggingface.co/docs/huggingface_hub/guides/download) |
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8. Profit! |
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9. Best results are obtained by putting a repetition_penalty(~1/0.85),temperature=0.7 in model.generate() for most LLaMA models |
