---
title: ScienceQA-IMG
canonical_url: "https://www.modelscope.cn/datasets/lmms-lab/ScienceQA-IMG"
md_url: "https://www.modelscope.cn/datasets/lmms-lab/ScienceQA-IMG.md"
repository: lmms-lab/ScienceQA-IMG
last_updated: 2024-11-21
license: "Apache License 2.0"
storage_size: "633 MB"
downloads: 3239
stars: 1
---

# ScienceQA-IMG

> ScienceQA-IMG - lmms-lab 在 ModelScope 开源的数据集。Large-scale Multi-modality Models Evaluation Suite

lmms-lab/ScienceQA-IMG 是 ModelScope 魔搭社区上的数据集，存储大小 633 MB，采用 Apache License 2.0 许可。

- **Repository**: lmms-lab/ScienceQA-IMG
- **License**: Apache License 2.0
- **Storage size**: 633 MB
- **Downloads**: 3239
- **Stars**: 1
- **Last updated**: 2024-11-21

Source: https://www.modelscope.cn/datasets/lmms-lab/ScienceQA-IMG

---

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

# 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}
}
```