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## How to Prepare Vicuna Weight | |
Vicuna is an open-source LLAMA-based LLM that has a performance close to ChatGPT. | |
We currently use the v0 version of Vicuna-13B. | |
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). | |
In case you have git-lfs installed (https://git-lfs.com), this can be done by | |
``` | |
git lfs install | |
git clone https://huggingface.co/lmsys/vicuna-13b-delta-v0 # more powerful, need at least 24G gpu memory | |
# or | |
git clone https://huggingface.co/lmsys/vicuna-7b-delta-v0 # smaller, need 12G gpu memory | |
``` | |
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.) | |
Then, you need to obtain the original LLAMA-7B or LLAMA-13B weights in the HuggingFace format | |
either following the instruction provided by HuggingFace | |
[here](https://huggingface.co/docs/transformers/main/model_doc/llama) or from the Internet. | |
When these two weights are ready, we can use tools from Vicuna’s team to create the real working weight. | |
First, Install their library that is compatible with v0 Vicuna by | |
``` | |
pip install git+https://github.com/lm-sys/[email protected] | |
``` | |
Then, run the following command to create the final working weight | |
``` | |
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/ | |
``` | |
Now you are good to go! | |