DocVQA

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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 [DocVQA](https://arxiv.org/abs/2007.00398). It is used in our `lmms-eval` pipeline to allow for one-click evaluations of large multi-modality models.

```
@article{mathew2020docvqa,
title={DocVQA: A Dataset for VQA on Document Images. CoRR abs/2007.00398 (2020)},
author={Mathew, Minesh and Karatzas, Dimosthenis and Manmatha, R and Jawahar, CV},
journal={arXiv preprint arXiv:2007.00398},
year={2020}
}
```

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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

本数据集为[DocVQA](https://arxiv.org/abs/2007.00398)的格式化版本，可集成于我们的`lmms-eval`评测流程中，支持大规模多模态模型的一键评测。

@article{mathew2020docvqa,
title={DocVQA：文档图像视觉问答（Visual Question Answering, VQA）数据集. CoRR abs/2007.00398（2020）},
author={Mathew, Minesh and Karatzas, Dimosthenis and Manmatha, R and Jawahar, CV},
journal={arXiv预印本 arXiv:2007.00398},
year={2020}
}

搜集汇总

背景与挑战

背景概述

DocVQA是用于大规模多模态模型评估的数据集，基于DocVQA原始版本格式化，支持通过lmms-eval管道对大型多模态模型进行一键评测。该数据集遵循Apache 2.0许可证，由lmms-lab维护。