---
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 EXL2 version of the [tigerbot-70b-chat-v4-4k](https://huggingface.co/TigerResearch/tigerbot-70b-chat-v4-4k).

It was quantized to 4bit using: https://github.com/turboderp/exllamav2

## 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

infer with exllamav2
```
# install exllamav2
git clone https://github.com/turboderp/exllamav2
cd exllamav2
pip install -r requirements.txt

# infer command
CUDA_VISIBLE_DEVICES=0 python other_infer/exllamav2_hf_infer.py --model_path TigerResearch/tigerbot-70b-chat-v4-4bit-exl2
```