SEED-Bench

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# Large-scale Multi-modality Models Evaluation Suite

> Accelerating the development of large-scale multi-modality models (LMMs) with `lmms-eval`

🏠 [Homepage](https://lmms-lab.github.io/) | 📚 [Documentation](docs/README.md) | 🤗 [Huggingface Datasets](https://huggingface.co/lmms-lab)

# This Dataset

This is a formatted version of [SEED-Bench](https://github.com/AILab-CVC/SEED-Bench). It is used in our `lmms-eval` pipeline to allow for one-click evaluations of large multi-modality models.

```
@article{li2023seed,
title={Seed-bench: Benchmarking multimodal llms with generative comprehension},
author={Li, Bohao and Wang, Rui and Wang, Guangzhi and Ge, Yuying and Ge, Yixiao and Shan, Ying},
journal={arXiv preprint arXiv:2307.16125},
year={2023}
}
```

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<img src="https://i.postimg.cc/g0QRgMVv/WX20240228-113337-2x.png" width="100%" height="80%">
</p>

# 大规模多模态模型评测套件

> 借助`lmms-eval`加速大规模多模态模型（Large-scale Multi-modality Models, LMMs）的研发

🏠 [主页](https://lmms-lab.github.io/) | 📚 [文档](docs/README.md) | 🤗 [Huggingface 数据集仓库](https://huggingface.co/lmms-lab)

# 本数据集

本数据集是[SEED-Bench](https://github.com/AILab-CVC/SEED-Bench)的格式化版本，可集成至我们的`lmms-eval`流水线，实现大规模多模态模型的一键评测。

@article{li2023seed,
title={SEED-Bench：面向生成式理解能力的多模态大语言模型评测基准},
author={Li, Bohao and Wang, Rui and Wang, Guangzhi and Ge, Yuying and Ge, Yixiao and Shan, Ying},
journal={arXiv预印本 arXiv:2307.16125},
year={2023}
}

搜集汇总

背景与挑战

背景概述

SEED-Bench是一个大规模多模态模型评估套件，支持通过lmms-eval进行一键式评估，遵循Apache License 2.0许可，大小为27.16GB。