--- dataset_info: features: - name: image dtype: image - name: image_coco_url dtype: string - name: image_date_captured dtype: string - name: image_file_name dtype: string - name: image_height dtype: int32 - name: image_width dtype: int32 - name: image_id dtype: int32 - name: image_license dtype: int8 - name: image_open_images_id dtype: string - name: annotations_ids sequence: int32 - name: annotations_captions sequence: string splits: - name: validation num_bytes: 1421862846.0 num_examples: 4500 - name: test num_bytes: 3342844310.0 num_examples: 10600 download_size: 4761076789 dataset_size: 4764707156.0 configs: - config_name: default data_files: - split: validation path: data/validation-* - 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 [NoCaps](https://nocaps.org/). It is used in our `lmms-eval` pipeline to allow for one-click evaluations of large multi-modality models. ``` @inproceedings{Agrawal_2019, title={nocaps: novel object captioning at scale}, url={http://dx.doi.org/10.1109/ICCV.2019.00904}, DOI={10.1109/iccv.2019.00904}, booktitle={2019 IEEE/CVF International Conference on Computer Vision (ICCV)}, publisher={IEEE}, author={Agrawal, Harsh and Desai, Karan and Wang, Yufei and Chen, Xinlei and Jain, Rishabh and Johnson, Mark and Batra, Dhruv and Parikh, Devi and Lee, Stefan and Anderson, Peter}, year={2019}, month=oct } ```