tigerbot-7b-sft-v2-4bit

<div style="width: 100%;"> <img src="http://x-pai.algolet.com/bot/img/logo_core.png" alt="TigerBot" style="width: 20%; display: block; margin: auto;"> </div> <p align="center"> <font face="黑体" size=5"> A cutting-edge foundation for your very own LLM. </font> </p> <p align="center"> 🌐 <a href="https://tigerbot.com/" target="_blank">TigerBot</a> • 🤗 <a href="https://huggingface.co/TigerResearch" target="_blank">Hugging Face</a> </p>

This is a 4-bit GPTQ version of the Tigerbot 7B sft v2.

It was quantized to 4bit using: https://github.com/TigerResearch/TigerBot/tree/main/gptq

How to download and use this model in github: https://github.com/TigerResearch/TigerBot

Here are commands to clone the TigerBot and install.

conda create --name tigerbot python=3.8
conda activate tigerbot
conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia

git clone https://github.com/TigerResearch/TigerBot
cd TigerBot
pip install -r requirements.txt

Inference with command line interface

cd TigerBot/gptq
CUDA_VISIBLE_DEVICES=0 python tigerbot_infer.py TigerResearch/tigerbot-7b-sft-4bit-128g --wbits 4 --groupsize 128 --load TigerResearch/tigerbot-7b-sft-4bit-128g/tigerbot-7b-4bit-128g.pt