---
license: apache-2.0
language:
- zh
- en
---

<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-13b-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-13b-base
    git clone https://www.modelscope.cn/TigerResearch/tigerbot-13b-base-v2.git
    ```

  - 启动infer代码

    ```shell
    python infer.py --model_path tigerbot-13b-base(-v2) --model_type base --max_generate_length 64
    ```

------

# 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-13b-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-13b-base
    git clone https://www.modelscope.cn/TigerResearch/tigerbot-13b-base-v2.git
    ```

  - Run infer script

     ```shell
     python infer.py --model_path tigerbot-13b-base(-v2) --model_type base --max_generate_length 64
     ```
# [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-13b-base)

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 52.11   |
| ARC (25-shot)         | 53.84          |
| HellaSwag (10-shot)   | 77.05    |
| MMLU (5-shot)         | 53.57         |
| TruthfulQA (0-shot)   | 44.06   |
| Winogrande (5-shot)   | 74.98   |
| GSM8K (5-shot)        | 17.06        |
| DROP (3-shot)         | 44.21         |