fincompass


Namefincompass JSON
Version 0.1.2 PyPI version JSON
download
home_page
SummaryA comprehensive toolkit for large model evaluation
upload_time2023-08-21 10:09:58
maintainer
docs_urlNone
author
requires_python>=3.8.0
license
keywords ai nlp in-context learning
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls. 
            <div align="center">
  <img src="docs/zh_cn/_static/image/logo.svg" width="500px"/>
  <br />
  <br />

[![docs](https://readthedocs.org/projects/opencompass/badge)](https://opencompass.readthedocs.io/zh_CN)
[![license](https://img.shields.io/github/license/InternLM/opencompass.svg)](https://github.com/InternLM/opencompass/blob/main/LICENSE)

<!-- [![PyPI](https://badge.fury.io/py/opencompass.svg)](https://pypi.org/project/opencompass/) -->

[🌐Website](https://opencompass.org.cn/) |
[📘Documentation](https://opencompass.readthedocs.io/zh_CN/latest/index.html) |
[🛠️Installation](https://opencompass.readthedocs.io/zh_CN/latest/get_started.html) |
[🤔Reporting Issues](https://github.com/InternLM/opencompass/issues/new/choose)

[English](/README.md) | 简体中文

</div>

<p align="center">
    👋 加入我们的 <a href="https://discord.gg/xa29JuW87d" target="_blank">Discord</a> 和 <a href="https://github.com/InternLM/InternLM/assets/25839884/a6aad896-7232-4220-ac84-9e070c2633ce" target="_blank">微信社区</a>
</p>

欢迎来到OpenCompass！

就像指南针在我们的旅程中为我们导航一样，我们希望OpenCompass能够帮助你穿越评估大型语言模型的重重迷雾。OpenCompass提供丰富的算法和功能支持，期待OpenCompass能够帮助社区更便捷地对NLP模型的性能进行公平全面的评估。

## 介绍

OpenCompass 是面向大模型评测的一站式平台。其主要特点如下：

- **开源可复现**：提供公平、公开、可复现的大模型评测方案

- **全面的能力维度**：五大维度设计，提供 50+ 个数据集约 30 万题的的模型评测方案，全面评估模型能力

- **丰富的模型支持**：已支持 20+ HuggingFace 及 API 模型

- **分布式高效评测**：一行命令实现任务分割和分布式评测，数小时即可完成千亿模型全量评测

- **多样化评测范式**：支持零样本、小样本及思维链评测，结合标准型或对话型提示词模板，轻松激发各种模型最大性能

- **灵活化拓展**：想增加新模型或数据集？想要自定义更高级的任务分割策略，甚至接入新的集群管理系统？OpenCompass 的一切均可轻松扩展！

## 性能榜单

我们将陆续提供开源模型和API模型的具体性能榜单，请见 [OpenCompass Leaderbaord](https://opencompass.org.cn/rank) 。如需加入评测，请提供模型仓库地址或标准的 API 接口至邮箱  `opencompass@pjlab.org.cn`.

[![image](https://github.com/InternLM/opencompass/assets/13503330/76237116-a9dd-4207-abef-7ff73b89568a)](https://opencompass.org.cn/rank)

## 数据集支持

<table align="center">
  <tbody>
    <tr align="center" valign="bottom">
      <td>
        <b>语言</b>
      </td>
      <td>
        <b>知识</b>
      </td>
      <td>
        <b>推理</b>
      </td>
      <td>
        <b>学科</b>
      </td>
      <td>
        <b>理解</b>
      </td>
    </tr>
    <tr valign="top">
      <td>
<details open>
<summary><b>字词释义</b></summary>

- WiC
- SummEdits

</details>

<details open>
<summary><b>成语习语</b></summary>

- CHID

</details>

<details open>
<summary><b>语义相似度</b></summary>

- AFQMC
- BUSTM

</details>

<details open>
<summary><b>指代消解</b></summary>

- CLUEWSC
- WSC
- WinoGrande

</details>

<details open>
<summary><b>翻译</b></summary>

- Flores

</details>
      </td>
      <td>
<details open>
<summary><b>知识问答</b></summary>

- BoolQ
- CommonSenseQA
- NaturalQuestion
- TrivialQA

</details>

<details open>
<summary><b>多语种问答</b></summary>

- TyDi-QA

</details>
      </td>
      <td>
<details open>
<summary><b>文本蕴含</b></summary>

- CMNLI
- OCNLI
- OCNLI_FC
- AX-b
- AX-g
- CB
- RTE

</details>

<details open>
<summary><b>常识推理</b></summary>

- StoryCloze
- StoryCloze-CN（即将上线）
- COPA
- ReCoRD
- HellaSwag
- PIQA
- SIQA

</details>

<details open>
<summary><b>数学推理</b></summary>

- MATH
- GSM8K

</details>

<details open>
<summary><b>定理应用</b></summary>

- TheoremQA

</details>

<details open>
<summary><b>代码</b></summary>

- HumanEval
- MBPP

</details>

<details open>
<summary><b>综合推理</b></summary>

- BBH

</details>
      </td>
      <td>
<details open>
<summary><b>初中/高中/大学/职业考试</b></summary>

- GAOKAO-2023
- CEval
- AGIEval
- MMLU
- GAOKAO-Bench
- MMLU-CN (即将上线)
- ARC

</details>
      </td>
      <td>
<details open>
<summary><b>阅读理解</b></summary>

- C3
- CMRC
- DRCD
- MultiRC
- RACE

</details>

<details open>
<summary><b>内容总结</b></summary>

- CSL
- LCSTS
- XSum

</details>

<details open>
<summary><b>内容分析</b></summary>

- EPRSTMT
- LAMBADA
- TNEWS

</details>
      </td>
    </tr>
</td>
    </tr>
  </tbody>
</table>

## 模型支持

<table align="center">
  <tbody>
    <tr align="center" valign="bottom">
      <td>
        <b>开源模型</b>
      </td>
      <td>
        <b>API 模型</b>
      </td>
      <!-- <td>
        <b>自定义模型</b>
      </td> -->
    </tr>
    <tr valign="top">
      <td>

- LLaMA
- Vicuna
- Alpaca
- Baichuan
- WizardLM
- ChatGLM-6B
- ChatGLM2-6B
- MPT
- Falcon
- TigerBot
- MOSS
- ……

</td>
<td>

- OpenAI
- Claude (即将推出)
- PaLM (即将推出)
- ……

</td>
<!-- <td>

- GLM
- ……

</td> -->
</tr>
  </tbody>
</table>

## 安装

下面展示了快速安装的步骤。有部分第三方功能可能需要额外步骤才能正常运行，详细步骤请参考[安装指南](https://opencompass.readthedocs.io/zh_cn/latest/get_started.html)。

```Python
conda create --name opencompass python=3.10 pytorch torchvision pytorch-cuda -c nvidia -c pytorch -y
conda activate opencompass
git clone https://github.com/InternLM/opencompass opencompass
cd opencompass
pip install -e .
# 下载数据集到 data/ 处
wget https://github.com/InternLM/opencompass/releases/download/0.1.0/OpenCompassData.zip
unzip OpenCompassData.zip
```

## 评测

请阅读[快速上手](https://opencompass.readthedocs.io/zh_CN/latest/get_started.html#id2)了解如何运行一个评测任务。

## 致谢

该项目部分的代码引用并修改自 [OpenICL](https://github.com/Shark-NLP/OpenICL)。

## 引用

```bibtex
@misc{2023opencompass,
    title={OpenCompass: A Universal Evaluation Platform for Foundation Models},
    author={OpenCompass Contributors},
    howpublished = {\url{https://github.com/InternLM/OpenCompass}},
    year={2023}
}
```

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**\u591a\u6837\u5316\u8bc4\u6d4b\u8303\u5f0f**\uff1a\u652f\u6301\u96f6\u6837\u672c\u3001\u5c0f\u6837\u672c\u53ca\u601d\u7ef4\u94fe\u8bc4\u6d4b\uff0c\u7ed3\u5408\u6807\u51c6\u578b\u6216\u5bf9\u8bdd\u578b\u63d0\u793a\u8bcd\u6a21\u677f\uff0c\u8f7b\u677e\u6fc0\u53d1\u5404\u79cd\u6a21\u578b\u6700\u5927\u6027\u80fd\n\n- **\u7075\u6d3b\u5316\u62d3\u5c55**\uff1a\u60f3\u589e\u52a0\u65b0\u6a21\u578b\u6216\u6570\u636e\u96c6\uff1f\u60f3\u8981\u81ea\u5b9a\u4e49\u66f4\u9ad8\u7ea7\u7684\u4efb\u52a1\u5206\u5272\u7b56\u7565\uff0c\u751a\u81f3\u63a5\u5165\u65b0\u7684\u96c6\u7fa4\u7ba1\u7406\u7cfb\u7edf\uff1fOpenCompass \u7684\u4e00\u5207\u5747\u53ef\u8f7b\u677e\u6269\u5c55\uff01\n\n## \u6027\u80fd\u699c\u5355\n\n\u6211\u4eec\u5c06\u9646\u7eed\u63d0\u4f9b\u5f00\u6e90\u6a21\u578b\u548cAPI\u6a21\u578b\u7684\u5177\u4f53\u6027\u80fd\u699c\u5355\uff0c\u8bf7\u89c1 [OpenCompass Leaderbaord](https://opencompass.org.cn/rank) \u3002\u5982\u9700\u52a0\u5165\u8bc4\u6d4b\uff0c\u8bf7\u63d0\u4f9b\u6a21\u578b\u4ed3\u5e93\u5730\u5740\u6216\u6807\u51c6\u7684 API \u63a5\u53e3\u81f3\u90ae\u7bb1  `opencompass@pjlab.org.cn`.\n\n[![image](https://github.com/InternLM/opencompass/assets/13503330/76237116-a9dd-4207-abef-7ff73b89568a)](https://opencompass.org.cn/rank)\n\n## \u6570\u636e\u96c6\u652f\u6301\n\n<table align=\"center\">\n  <tbody>\n    <tr align=\"center\" valign=\"bottom\">\n      <td>\n        <b>\u8bed\u8a00</b>\n      </td>\n      <td>\n        <b>\u77e5\u8bc6</b>\n      </td>\n      <td>\n        <b>\u63a8\u7406</b>\n      </td>\n      <td>\n        <b>\u5b66\u79d1</b>\n      </td>\n      <td>\n        <b>\u7406\u89e3</b>\n      </td>\n    </tr>\n    <tr valign=\"top\">\n      <td>\n<details open>\n<summary><b>\u5b57\u8bcd\u91ca\u4e49</b></summary>\n\n- WiC\n- SummEdits\n\n</details>\n\n<details open>\n<summary><b>\u6210\u8bed\u4e60\u8bed</b></summary>\n\n- CHID\n\n</details>\n\n<details open>\n<summary><b>\u8bed\u4e49\u76f8\u4f3c\u5ea6</b></summary>\n\n- AFQMC\n- BUSTM\n\n</details>\n\n<details open>\n<summary><b>\u6307\u4ee3\u6d88\u89e3</b></summary>\n\n- CLUEWSC\n- WSC\n- WinoGrande\n\n</details>\n\n<details open>\n<summary><b>\u7ffb\u8bd1</b></summary>\n\n- Flores\n\n</details>\n      </td>\n      <td>\n<details open>\n<summary><b>\u77e5\u8bc6\u95ee\u7b54</b></summary>\n\n- BoolQ\n- CommonSenseQA\n- NaturalQuestion\n- TrivialQA\n\n</details>\n\n<details open>\n<summary><b>\u591a\u8bed\u79cd\u95ee\u7b54</b></summary>\n\n- TyDi-QA\n\n</details>\n      </td>\n      <td>\n<details open>\n<summary><b>\u6587\u672c\u8574\u542b</b></summary>\n\n- CMNLI\n- OCNLI\n- OCNLI_FC\n- AX-b\n- AX-g\n- CB\n- RTE\n\n</details>\n\n<details open>\n<summary><b>\u5e38\u8bc6\u63a8\u7406</b></summary>\n\n- StoryCloze\n- StoryCloze-CN\uff08\u5373\u5c06\u4e0a\u7ebf\uff09\n- COPA\n- ReCoRD\n- HellaSwag\n- PIQA\n- SIQA\n\n</details>\n\n<details open>\n<summary><b>\u6570\u5b66\u63a8\u7406</b></summary>\n\n- MATH\n- GSM8K\n\n</details>\n\n<details open>\n<summary><b>\u5b9a\u7406\u5e94\u7528</b></summary>\n\n- TheoremQA\n\n</details>\n\n<details open>\n<summary><b>\u4ee3\u7801</b></summary>\n\n- HumanEval\n- MBPP\n\n</details>\n\n<details open>\n<summary><b>\u7efc\u5408\u63a8\u7406</b></summary>\n\n- BBH\n\n</details>\n      </td>\n      <td>\n<details open>\n<summary><b>\u521d\u4e2d/\u9ad8\u4e2d/\u5927\u5b66/\u804c\u4e1a\u8003\u8bd5</b></summary>\n\n- GAOKAO-2023\n- CEval\n- AGIEval\n- MMLU\n- GAOKAO-Bench\n- MMLU-CN (\u5373\u5c06\u4e0a\u7ebf)\n- ARC\n\n</details>\n      </td>\n      <td>\n<details open>\n<summary><b>\u9605\u8bfb\u7406\u89e3</b></summary>\n\n- C3\n- CMRC\n- DRCD\n- MultiRC\n- RACE\n\n</details>\n\n<details open>\n<summary><b>\u5185\u5bb9\u603b\u7ed3</b></summary>\n\n- CSL\n- LCSTS\n- XSum\n\n</details>\n\n<details open>\n<summary><b>\u5185\u5bb9\u5206\u6790</b></summary>\n\n- EPRSTMT\n- LAMBADA\n- TNEWS\n\n</details>\n      </td>\n    </tr>\n</td>\n    </tr>\n  </tbody>\n</table>\n\n## \u6a21\u578b\u652f\u6301\n\n<table align=\"center\">\n  <tbody>\n    <tr align=\"center\" valign=\"bottom\">\n      <td>\n        <b>\u5f00\u6e90\u6a21\u578b</b>\n      </td>\n      <td>\n        <b>API \u6a21\u578b</b>\n      </td>\n      <!-- <td>\n        <b>\u81ea\u5b9a\u4e49\u6a21\u578b</b>\n      </td> -->\n    </tr>\n    <tr valign=\"top\">\n      <td>\n\n- LLaMA\n- Vicuna\n- Alpaca\n- Baichuan\n- WizardLM\n- ChatGLM-6B\n- ChatGLM2-6B\n- MPT\n- Falcon\n- TigerBot\n- MOSS\n- \u2026\u2026\n\n</td>\n<td>\n\n- OpenAI\n- Claude (\u5373\u5c06\u63a8\u51fa)\n- PaLM (\u5373\u5c06\u63a8\u51fa)\n- \u2026\u2026\n\n</td>\n<!-- <td>\n\n- GLM\n- \u2026\u2026\n\n</td> -->\n</tr>\n  </tbody>\n</table>\n\n## \u5b89\u88c5\n\n\u4e0b\u9762\u5c55\u793a\u4e86\u5feb\u901f\u5b89\u88c5\u7684\u6b65\u9aa4\u3002\u6709\u90e8\u5206\u7b2c\u4e09\u65b9\u529f\u80fd\u53ef\u80fd\u9700\u8981\u989d\u5916\u6b65\u9aa4\u624d\u80fd\u6b63\u5e38\u8fd0\u884c\uff0c\u8be6\u7ec6\u6b65\u9aa4\u8bf7\u53c2\u8003[\u5b89\u88c5\u6307\u5357](https://opencompass.readthedocs.io/zh_cn/latest/get_started.html)\u3002\n\n```Python\nconda create --name opencompass python=3.10 pytorch torchvision pytorch-cuda -c nvidia -c pytorch -y\nconda activate opencompass\ngit clone https://github.com/InternLM/opencompass opencompass\ncd opencompass\npip install -e .\n# \u4e0b\u8f7d\u6570\u636e\u96c6\u5230 data/ \u5904\nwget https://github.com/InternLM/opencompass/releases/download/0.1.0/OpenCompassData.zip\nunzip OpenCompassData.zip\n```\n\n## \u8bc4\u6d4b\n\n\u8bf7\u9605\u8bfb[\u5feb\u901f\u4e0a\u624b](https://opencompass.readthedocs.io/zh_CN/latest/get_started.html#id2)\u4e86\u89e3\u5982\u4f55\u8fd0\u884c\u4e00\u4e2a\u8bc4\u6d4b\u4efb\u52a1\u3002\n\n## \u81f4\u8c22\n\n\u8be5\u9879\u76ee\u90e8\u5206\u7684\u4ee3\u7801\u5f15\u7528\u5e76\u4fee\u6539\u81ea [OpenICL](https://github.com/Shark-NLP/OpenICL)\u3002\n\n## \u5f15\u7528\n\n```bibtex\n@misc{2023opencompass,\n    title={OpenCompass: A Universal Evaluation Platform for Foundation Models},\n    author={OpenCompass Contributors},\n    howpublished = {\\url{https://github.com/InternLM/OpenCompass}},\n    year={2023}\n}\n```\n",
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