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36 lines
1.6 KiB
Markdown
36 lines
1.6 KiB
Markdown
## How to Prepare Vicuna Weight
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Vicuna is an open-source LLAMA-based LLM that has a performance close to ChatGPT.
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We currently use the v0 version of Vicuna-13B.
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To prepare Vicuna’s weight, first download Vicuna’s **delta** weight from [https://huggingface.co/lmsys/vicuna-13b-delta-v0](https://huggingface.co/lmsys/vicuna-13b-delta-v0).
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In case you have git-lfs installed (https://git-lfs.com), this can be done by
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```
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git lfs install
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git clone https://huggingface.co/lmsys/vicuna-13b-delta-v0 # more powerful, need at least 24G gpu memory
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# or
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git clone https://huggingface.co/lmsys/vicuna-7b-delta-v0 # smaller, need 12G gpu memory
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```
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Note that this is not directly the working weight, but the difference between the working weight and the original weight of LLAMA-13B. (Due to LLAMA’s rules, we cannot distribute the weight of LLAMA.)
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Then, you need to obtain the original LLAMA-7B or LLAMA-13B weights in the HuggingFace format
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either following the instruction provided by HuggingFace
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[here](https://huggingface.co/docs/transformers/main/model_doc/llama) or from the Internet.
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When these two weights are ready, we can use tools from Vicuna’s team to create the real working weight.
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First, Install their library that is compatible with v0 Vicuna by
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```
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pip install git+https://github.com/lm-sys/FastChat.git@v0.1.10
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```
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Then, run the following command to create the final working weight
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```
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python -m fastchat.model.apply_delta --base /path/to/llama-13bOR7b-hf/ --target /path/to/save/working/vicuna/weight/ --delta /path/to/vicuna-13bOR7b-delta-v0/
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```
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Now you are good to go!
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