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Converted with https://github.com/qwopqwop200/GPTQ-for-LLaMa All models tested on A100-80G *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.

Installation instructions as mentioned in above repo:

  1. Install Anaconda and create a venv with python 3.8
  2. Install pytorch(tested with torch-1.13-cu116)
  3. Install Transformers library (you'll need the latest transformers with this PR : https://github.com/huggingface/transformers/pull/21955 ).
  4. Install sentencepiece from pip
  5. Run python cuda_setup.py install in venv
  6. You can either convert the llama models yourself with the instructions from GPTQ-for-llama repo
  7. or directly use these weights by individually downloading them following these instructions (https://huggingface.co/docs/huggingface_hub/guides/download)
  8. Profit!
  9. Best results are obtained by putting a repetition_penalty(~1/0.85),temperature=0.7 in model.generate() for most LLaMA models
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