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---
license: apache-2.0
language:
- zh
- en
---
<div style="width: 100%;">
<p align="center" width="20%">
<img src="http://x-pai.algolet.com/bot/img/logo_core.png" alt="TigerBot" width="20%", style="display: block; margin: auto;"></img>
</p>
</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://github.com/TigerResearch/TigerBot" target="_blank">Github</a> • 🌐 <a href="https://tigerbot.com/" target="_blank">TigerBot</a> • 🤗 <a href="https://huggingface.co/TigerResearch" target="_blank">Hugging Face</a>
</p>
# 快速开始
- 方法1，通过transformers使用
- 下载 TigerBot Repo
```shell
git clone https://github.com/TigerResearch/TigerBot.git
```
- 启动infer代码
```shell
python infer.py --model_path TigerResearch/tigerbot-70b-base-v1 --model_type base
```
- 方法2:
- 下载 TigerBot Repo
```shell
git clone https://github.com/TigerResearch/TigerBot.git
```
- 安装git lfs： `git lfs install`
- 通过huggingface或modelscope平台下载权重
```shell
git clone https://huggingface.co/TigerResearch/tigerbot-70b-base-v1
git clone https://www.modelscope.cn/TigerResearch/tigerbot-70b-base-v1.git
```
- 启动infer代码
```shell
python infer.py --model_path tigerbot-70b-base-v1 --model_type base
```
------
# Quick Start
- Method 1, use through transformers
- Clone TigerBot Repo
```shell
git clone https://github.com/TigerResearch/TigerBot.git
```
- Run infer script
```shell
python infer.py --model_path TigerResearch/tigerbot-70b-base-v1 --model_type base
```
- Method 2:
- Clone TigerBot Repo
```shell
git clone https://github.com/TigerResearch/TigerBot.git
```
- install git lfs： `git lfs install`
- Download weights from huggingface or modelscope
```shell
git clone https://huggingface.co/TigerResearch/tigerbot-70b-base-v1
git clone https://www.modelscope.cn/TigerResearch/tigerbot-70b-base-v1.git
```
- Run infer script
```shell
python infer.py --model_path tigerbot-70b-base-v1 --model_type base
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_TigerResearch__tigerbot-70b-base)
| Metric | Value |
|-----------------------|---------------------------|
| Avg. | 62.1 |
| ARC (25-shot) | 62.46 |
| HellaSwag (10-shot) | 83.61 |
| MMLU (5-shot) | 65.49 |
| TruthfulQA (0-shot) | 52.76 |
| Winogrande (5-shot) | 80.19 |
| GSM8K (5-shot) | 37.76 |
| DROP (3-shot) | 52.45 |
|