Interprete os detalhes e requisitos necessários para a instalação e gere uma lista de recursos e passos para a instalação. Em português.

Install
Method 1: With pip
pip3 install fschat
Method 2: From source
Clone this repository and navigate to the FastChat folder
git clone https://github.com/lm-sys/FastChat.git
cd FastChat
If you are running on NAME_1:

brew install rust cmake
Install Package
pip3 install --upgrade pip  # enable PEP 660 support
pip3 install -e .
Vicuna Weights
We release Vicuna weights as delta weights to comply with the LLaMA model license. You can add our delta to the original LLaMA weights to obtain the Vicuna weights. Instructions:

Get the original LLaMA weights in the huggingface format by following the instructions here.
Use the following scripts to get Vicuna weights by applying our delta. They will automatically download delta weights from our Hugging Face account.
NOTE: Weights v1.1 are only compatible with transformers>=4.28.0 and fschat >= 0.2.0. Please update your local packages accordingly. If you follow the above commands to do a fresh install, then you should get all the correct versions.

Vicuna-7B
This conversion command needs around 30 GB of CPU RAM. See the "Low CPU Memory Conversion" section below if you do not have enough memory.

python3 -m fastchat.model.apply_delta \
    --base /path/to/llama-7b \
    --target /output/path/to/vicuna-7b \
    --delta lmsys/vicuna-7b-delta-v1.1
Vicuna-13B
This conversion command needs around 60 GB of CPU RAM. See the "Low CPU Memory Convers Your entire response should be in English, and in all capital letters.
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