README.md

---
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-*
---


<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 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 }
```