MINT-1T is an open-source Multimodal INTerleaved dataset with one trillion text tokens and three billion images, a 10x scale-up from existing open-source datasets. Additionally, we include previously untapped sources such as PDFs and ArXiv papers. We are putting the final touches on MINT-1T and will open-source the dataset soon!
- We released our technical report.
If you found our work useful, please consider citing:
@article{awadalla2024mint1t,
title={MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens},
author={Anas Awadalla and Le Xue and Oscar Lo and Manli Shu and Hannah Lee and Etash Kumar Guha and Matt Jordan and Sheng Shen and Mohamed Awadalla and Silvio Savarese and Caiming Xiong and Ran Xu and Yejin Choi and Ludwig Schmidt},
year={2024}
}