--- dataset_info: features: - name: answer dtype: string - name: choice_a dtype: string - name: choice_b dtype: string - name: choice_c dtype: string - name: choice_d dtype: string - name: data_id sequence: string - name: data_type dtype: string - name: data_source dtype: string - name: level dtype: string - name: question dtype: string - name: question_id dtype: string - name: question_type_id dtype: int16 - name: subpart dtype: string - name: version dtype: string - name: captions-sharecaptioner dtype: string - name: captions-llava dtype: string - name: captions-phi dtype: string splits: - name: test num_bytes: 72823903 num_examples: 24371 download_size: 29541033 dataset_size: 72823903 configs: - config_name: default data_files: - split: test path: data/test-* ---

# 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-2](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{li2023seed2, title={SEED-Bench-2: Benchmarking Multimodal Large Language Models}, author={Li, Bohao and Ge, Yuying and Ge, Yixiao and Wang, Guangzhi and Wang, Rui and Zhang, Ruimao and Shan, Ying}, journal={arXiv preprint arXiv:2311.17092}, year={2023} } ```