Update README.md
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README.md
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README.md
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@ -34,6 +34,8 @@ It's fast on a 3070 Ti mobile. Uses 5-6 GB of GPU RAM.
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* Added Flash attention support. (Use --flash-attention)
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* Added Triton backend to support model using groupsize and act-order. (Use --backend=triton)
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* Added g_idx support in cuda backend (need recompile cuda kernel)
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* Added xformers support
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* Removed triton, flash-atten from requirements.txt for compatibility
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# Requirements
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gptq-for-llama <br>
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@ -102,3 +104,17 @@ python server.py
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It seems that we can apply a monkey patch for llama model. To use it, simply download the file from [MonkeyPatch](https://github.com/lm-sys/FastChat/blob/daa9c11080ceced2bd52c3e0027e4f64b1512683/fastchat/train/llama_flash_attn_monkey_patch.py). And also, flash-attention is needed, and currently do not support pytorch 2.0.
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Just add --flash-attention to use it for finetuning.
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# Xformers
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* Install
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```
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pip install xformers
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```
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* Usage
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```
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from monkeypatch.llama_attn_hijack_xformers import hijack_llama_attention
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hijack_llama_attention()
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```
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