---
license: apache-2.0
---
<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-180b-research](https://huggingface.co/TigerResearch/tigerbot-180b-research).

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=0,1 python tigerbot_infer.py ${MODEL_DIR} --wbits 4 --groupsize 128 --load "{MODEL_DIR}/tigerbot-4bit-128g-*.pt"
```