textvqa

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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 [TextVQA](https://textvqa.org/). It is used in our `lmms-eval` pipeline to allow for one-click evaluations of large multi-modality models.

```
@inproceedings{singh2019towards,
title={Towards vqa models that can read},
author={Singh, Amanpreet and Natarajan, Vivek and Shah, Meet and Jiang, Yu and Chen, Xinlei and Batra, Dhruv and Parikh, Devi and Rohrbach, Marcus},
booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
pages={8317--8326},
year={2019}
}
```

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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](https://huggingface.co/lmms-lab)

# 本数据集

本数据集是[TextVQA](https://textvqa.org/)的格式化版本，可集成至我们的`lmms-eval`评测流水线中，实现大规模多模态模型的一键式评测。

@inproceedings{singh2019towards,
title={Towards vqa models that can read},
author={Singh, Amanpreet and Natarajan, Vivek and Shah, Meet and Jiang, Yu and Chen, Xinlei and Batra, Dhruv and Parikh, Devi and Rohrbach, Marcus},
booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
pages={8317--8326},
year={2019}
}

搜集汇总

背景与挑战

背景概述

该数据集是TextVQA的格式化版本，专用于lmms-eval流水线，以实现大型多模态模型的一键评估。它采用Apache 2.0许可证，大小为8.10GB，最近更新于2024年11月。