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Co-authored-by: gaotongxiao <[email protected]>
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14 changes: 8 additions & 6 deletions README.md
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Expand Up @@ -27,19 +27,21 @@ to **OpenCompass**!

Just like a compass guides us on our journey, OpenCompass will guide you through the complex landscape of evaluating large language models. With its powerful algorithms and intuitive interface, OpenCompass makes it easy to assess the quality and effectiveness of your NLP models.

> **🔥 Attention**<br />
> We launch the OpenCompass Collabration project, welcome to support diverse evaluation benchmarks into OpenCompass!
> Clike [Issue](https://github.com/InternLM/opencompass/issues/248) for more information.
> Let's work together to build a more powerful OpenCompass toolkit!
## 🚀 What's New <a><img width="35" height="20" src="https://user-images.githubusercontent.com/12782558/212848161-5e783dd6-11e8-4fe0-bbba-39ffb77730be.png"></a>

- **\[2023.08.25\]** [**TigerBot**](https://github.com/TigerResearch/TigerBot) team adpots OpenCompass to evaluate their models systematically. We deeply appreciate the community's dedication to transparency and reproducibility in LLM evaluation.
- **\[2023.08.21\]** [**Lagent**](https://github.com/InternLM/lagent) has been released, which is a lightweight framework for building LLM-based agents. We are working with Lagent team to support the evaluation of general tool-use capability, stay tuned! 🔥🔥🔥.
- **\[2023.08.18\]** We have supported evaluation for **multi-modality learning**, include **MMBench, SEED-Bench, COCO-Caption, Flickr-30K, OCR-VQA, ScienceQA** and so on. Leaderboard is on the road. Feel free to try multi-modality evaluation with OpenCompass ! 🔥🔥🔥.
- **\[2023.08.18\]** [Dataset card](https://opencompass.org.cn/dataset-detail/MMLU) is now online. Welcome new evaluation benchmark OpenCompass !
- **\[2023.08.11\]** [Model comparison](https://opencompass.org.cn/model-compare/GPT-4,ChatGPT,LLaMA-2-70B,LLaMA-65B) is now online. We hope this feature offers deeper insights!
- **\[2023.08.11\]** We have supported [LEval](https://github.com/OpenLMLab/LEval).
- **\[2023.08.10\]** OpenCompass is compatible with [LMDeploy](https://github.com/InternLM/lmdeploy). Now you can follow this [instruction](https://opencompass.readthedocs.io/en/latest/advanced_guides/evaluation_turbomind.html#) to evaluate the accelerated models provide by the **Turbomind**.
- **\[2023.08.10\]** We have supported [Qwen-7B](https://github.com/QwenLM/Qwen-7B) and [XVERSE-13B](https://github.com/xverse-ai/XVERSE-13B) ! Go to our [leaderboard](https://opencompass.org.cn/leaderboard-llm) for more results! More models are welcome to join OpenCompass.
- **\[2023.08.09\]** Several new datasets(**CMMLU, TydiQA, SQuAD2.0, DROP**) are updated on our [leaderboard](https://opencompass.org.cn/leaderboard-llm)! More datasets are welcomed to join OpenCompass.
- **\[2023.08.07\]** We have added a [script](tools/eval_mmbench.py) for users to evaluate the inference results of [MMBench](https://opencompass.org.cn/MMBench)-dev.
- **\[2023.08.05\]** We have supported [GPT-4](https://openai.com/gpt-4)! Go to our [leaderboard](https://opencompass.org.cn/leaderboard-llm) for more results! More models are welcome to join OpenCompass.
- **\[2023.07.27\]** We have supported [CMMLU](https://github.com/haonan-li/CMMLU)! More datasets are welcome to join OpenCompass.

> [More](docs/en/notes/news.md)
## ✨ Introduction

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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。

> **🔥 注意**<br />
> 我们正式启动 OpenCompass 共建计划,诚邀社区用户为 OpenCompass 提供更具代表性和可信度的客观评测数据集!
> 点击 [Issue](https://github.com/InternLM/opencompass/issues/248) 获取更多数据集.
> 让我们携手共进,打造功能强大易用的大模型评测平台!
## 🚀 最新进展 <a><img width="35" height="20" src="https://user-images.githubusercontent.com/12782558/212848161-5e783dd6-11e8-4fe0-bbba-39ffb77730be.png"></a>

- **\[2023.08.25\]** 欢迎 [**TigerBot**](https://github.com/TigerResearch/TigerBot) 团队采用OpenCompass对模型进行系统评估。我们非常感谢社区在提升LLM评估的透明度和可复现性上所做的努力。
🔥🔥🔥.
- **\[2023.08.21\]** [**Lagent**](https://github.com/InternLM/lagent) 正式发布,它是一个轻量级、开源的基于大语言模型的智能体(agent)框架。我们正与Lagent团队紧密合作,推进支持基于Lagent的大模型工具能力评测 ! 🔥🔥🔥.
- **\[2023.08.18\]** OpenCompass现已支持**多模态评测**,支持10+多模态评测数据集,包括 **MMBench, SEED-Bench, COCO-Caption, Flickr-30K, OCR-VQA, ScienceQA** 等. 多模态评测榜单即将上线,敬请! 🔥🔥🔥.
- **\[2023.08.18\]** OpenCompass现已支持**多模态评测**,支持10+多模态评测数据集,包括 **MMBench, SEED-Bench, COCO-Caption, Flickr-30K, OCR-VQA, ScienceQA** 等. 多模态评测榜单即将上线,敬请期待!
- **\[2023.08.18\]** [数据集页面](https://opencompass.org.cn/dataset-detail/MMLU) 现已在OpenCompass官网上线,欢迎更多社区评测数据集加入OpenCompass !
- **\[2023.08.11\]** 官网榜单上新增了[模型对比](https://opencompass.org.cn/model-compare/GPT-4,ChatGPT,LLaMA-2-70B,LLaMA-65B)功能,希望该功能可以协助提供更多发现!
- **\[2023.08.11\]** 新增了 [LEval](https://github.com/OpenLMLab/LEval) 评测支持.
- **\[2023.08.10\]** OpenCompass 现已适配 [LMDeploy](https://github.com/InternLM/lmdeploy). 请参考 [评测指南](https://opencompass.readthedocs.io/zh_CN/latest/advanced_guides/evaluation_turbomind.html)**Turbomind** 加速后的模型进行评估.
- **\[2023.08.10\]** [Qwen-7B](https://github.com/QwenLM/Qwen-7B)[XVERSE-13B](https://github.com/xverse-ai/XVERSE-13B)的评测结果已更新在 OpenCompass [大语言模型评测榜单](https://opencompass.org.cn/leaderboard-llm)!
- **\[2023.08.09\]** 更新更多评测数据集(**CMMLU, TydiQA, SQuAD2.0, DROP**) ,请登录 [大语言模型评测榜单](https://opencompass.org.cn/leaderboard-llm) 查看更多结果! 欢迎添加你的评测数据集到OpenCompass.
- **\[2023.08.07\]** 新增了 [MMBench 评测脚本](tools/eval_mmbench.py) 以支持用户自行获取 [MMBench](https://opencompass.org.cn/MMBench)-dev 的测试结果.
- **\[2023.08.05\]** [GPT-4](https://openai.com/gpt-4) 的评测结果已更新在 OpenCompass [大语言模型评测榜单](https://opencompass.org.cn/leaderboard-llm)!
- **\[2023.07.27\]** 新增了 [CMMLU](https://github.com/haonan-li/CMMLU)! 欢迎更多的数据集加入 OpenCompass.

> [更多](docs/zh_cn/notes/news.md)
## ✨ 介绍

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# News

- **\[2023.08.10\]** OpenCompass is compatible with [LMDeploy](https://github.com/InternLM/lmdeploy). Now you can follow this [instruction](https://opencompass.readthedocs.io/en/latest/advanced_guides/evaluation_turbomind.html#) to evaluate the accelerated models provide by the **Turbomind**.
- **\[2023.08.10\]** We have supported [Qwen-7B](https://github.com/QwenLM/Qwen-7B) and [XVERSE-13B](https://github.com/xverse-ai/XVERSE-13B) ! Go to our [leaderboard](https://opencompass.org.cn/leaderboard-llm) for more results! More models are welcome to join OpenCompass.
- **\[2023.08.09\]** Several new datasets(**CMMLU, TydiQA, SQuAD2.0, DROP**) are updated on our [leaderboard](https://opencompass.org.cn/leaderboard-llm)! More datasets are welcomed to join OpenCompass.
- **\[2023.08.07\]** We have added a [script](tools/eval_mmbench.py) for users to evaluate the inference results of [MMBench](https://opencompass.org.cn/MMBench)-dev.
- **\[2023.08.05\]** We have supported [GPT-4](https://openai.com/gpt-4)! Go to our [leaderboard](https://opencompass.org.cn/leaderboard-llm) for more results! More models are welcome to join OpenCompass.
- **\[2023.07.27\]** We have supported [CMMLU](https://github.com/haonan-li/CMMLU)! More datasets are welcome to join OpenCompass.
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# 新闻

- **\[2023.08.10\]** OpenCompass 现已适配 [LMDeploy](https://github.com/InternLM/lmdeploy). 请参考 [评测指南](https://opencompass.readthedocs.io/zh_CN/latest/advanced_guides/evaluation_turbomind.html)**Turbomind** 加速后的模型进行评估.
- **\[2023.08.10\]** [Qwen-7B](https://github.com/QwenLM/Qwen-7B)[XVERSE-13B](https://github.com/xverse-ai/XVERSE-13B)的评测结果已更新在 OpenCompass [大语言模型评测榜单](https://opencompass.org.cn/leaderboard-llm)!
- **\[2023.08.09\]** 更新更多评测数据集(**CMMLU, TydiQA, SQuAD2.0, DROP**) ,请登录 [大语言模型评测榜单](https://opencompass.org.cn/leaderboard-llm) 查看更多结果! 欢迎添加你的评测数据集到OpenCompass.
- **\[2023.08.07\]** 新增了 [MMBench 评测脚本](tools/eval_mmbench.py) 以支持用户自行获取 [MMBench](https://opencompass.org.cn/MMBench)-dev 的测试结果.
- **\[2023.08.05\]** [GPT-4](https://openai.com/gpt-4) 的评测结果已更新在 OpenCompass [大语言模型评测榜单](https://opencompass.org.cn/leaderboard-llm)!
- **\[2023.07.27\]** 新增了 [CMMLU](https://github.com/haonan-li/CMMLU)! 欢迎更多的数据集加入 OpenCompass.

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