ScienceQA-IMG

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<img src="https://i.postimg.cc/g0QRgMVv/WX20240228-113337-2x.png" width="100%" height="80%">
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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 and filtered version of [derek-thomas/ScienceQA](https://huggingface.co/datasets/derek-thomas/ScienceQA) with only image instances. It is used in our `lmms-eval` pipeline to allow for one-click evaluations of large multi-modality models.

```
@inproceedings{lu2022learn,
title={Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering},
author={Lu, Pan and Mishra, Swaroop and Xia, Tony and Qiu, Liang and Chang, Kai-Wei and Zhu, Song-Chun and Tafjord, Oyvind and Clark, Peter and Ashwin Kalyan},
booktitle={The 36th Conference on Neural Information Processing Systems (NeurIPS)},
year={2022}
}
```

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<img src="https://i.postimg.cc/g0QRgMVv/WX20240228-113337-2x.png" width="100%" height="80%">
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# 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[derek-thomas/ScienceQA](https://huggingface.co/datasets/derek-thomas/ScienceQA)的格式化与筛选版本，仅保留图像实例。我们将其应用于`lmms-eval`流水线中，以实现大规模多模态模型的一键式评测。

@inproceedings{lu2022learn,
title={学会解释：面向科学问答的基于思维链的多模态推理},
author={Lu, Pan and Mishra, Swaroop and Xia, Tony and Qiu, Liang and Chang, Kai-Wei and Zhu, Song-Chun and Tafjord, Oyvind and Clark, Peter and Ashwin Kalyan},
booktitle={第36届神经信息处理系统大会（NeurIPS)},
year={2022}
}