
The MINT-1T dataset, the first open-source multimodal dataset containing one trillion tokens, has been released. This dataset includes 3.4 billion images sourced from diverse materials such as HTML, PDFs, and ArXiv papers. Developed in collaboration with SFResearch, the dataset aims to enhance training for multimodal AI models and is available on platforms like Hugging Face. The release has been positively received within the AI community, with researchers expressing enthusiasm for its potential applications in advancing multimodal reasoning and generation. In the first 48 hours post-launch, downloads of the MINT-1T dataset have been robust, reflecting significant interest from the research community.
48 hours in and MINT-1T dataset downloads are going strong. Thanks to the collaborative team from @UW and @Stanford that made our multimodal training dataset happen, especially Professors @YejinChoinka and @lschmidt3! 🙌 Dataset: https://t.co/FHKhkAURdN Blog:… https://t.co/tZkSrvsP2J
MINT-1T Dataset Released: A Multimodal Dataset with One Trillion Tokens to Build Large Multimodal Models https://t.co/TDPyzNArL5 #MINT1T #MultimodalDataset #AIResearch #DataDiversity #AIAdvancements #ai #news #llm #ml #research #ainews #innovation #artificialintelligence #mac… https://t.co/Mm9jzQo47S
You can find the MINT-1T dataset in the @huggingface Hub: https://t.co/mwMFUgYbTk An #opensource multimodal interleaved dataset with 1T tokens and 3.4G images from diverse sources such as HTML, PDFs, and ArXiv papers. https://t.co/tWLPZ1E318


