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---
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: OBELISC
size_categories:
- 100M<n<1B
---
# Dataset Card for OBELISC
## Dataset Description
- **Repository: https://github.com/huggingface/OBELISC**
- **Paper: OBELISC: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents**
- **Point of Contact: hugo@huggingface.co**
### Dataset Summary
`OBELISC` is an open, massive and curated collection of interleaved image-text web documents, containing 141M documents, 115B text tokens and 353M images.
### Languages
English
### Visualization of OBELISC documents
https://huggingface.co/spaces/HuggingFaceM4/obelisc_visualization
### GitHub repository
https://github.com/huggingface/OBELISC
## Terms of Use
By using the dataset, you agree to comply with the original licenses of the source content as well as the dataset license (CC-BY-4.0). Additionally, if you use this dataset to train a Machine Learning model, you agree to disclose your use of the dataset when releasing the model or an ML application using the model.
### Licensing Information
License CC-BY-4.0.
### Citation Information
If you are using this dataset, please cite
```
@inproceedings{
lauren{\c{c}}on2023obe,
title={OBELISC: 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}
}
``` |