---
dataset_info:
  features:
  - name: images
    sequence: string
  - name: metadata
    dtype: string
  - name: general_metadata
    dtype: string
  - name: texts
    sequence: string
  splits:
  - name: train
    num_bytes: 715724717192
    num_examples: 141047697
  download_size: 71520629655
  dataset_size: 715724717192
license: cc-by-4.0
language:
- en
pretty_name: OBELICS
size_categories:
- 100M<n<1B
---
# Dataset Card for OBELICS

## Dataset Description

- **Repository: https://github.com/huggingface/OBELICS**
- **Paper: OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents**
- **Point of Contact: hugo@huggingface.co**

### Dataset Summary

`OBELICS` is an open, massive and curated collection of interleaved image-text web documents, containing 141M documents, 115B tokens and 353M images.

### Languages

English

### Visualization of OBELICS documents

https://huggingface.co/spaces/HuggingFaceM4/obelics_visualization

### GitHub repository

https://github.com/huggingface/OBELICS

## Considerations for Using the Data

`OBELICS` is released under the Creative Commons Attribution (CC-BY) license. By using this dataset, you accept the terms of the CC-BY license. The authors bear no responsibility for any violations of rights or misuse of the data.

### Licensing Information

License CC-BY.

### Citation Information

If you are using this dataset, please cite
```
@inproceedings{
lauren{\c{c}}on2023obe,
title={OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents},
author={Hugo Lauren{\c{c}}on and Lucile Saulnier and L{\'e}o Tronchon and Stas Bekman and Amanpreet Singh and Anton Lozhkov and Thomas Wang and Siddharth Karamcheti and Alexander M Rush and Douwe Kiela and Matthieu Cord and Victor Sanh},
year={2023}
}
```