Model Hub
Browse PQC-verified AI models, datasets, and tools
🍃 MINT-1T:Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens 🍃 MINT-1T is an open-source Multimodal INTerleaved dataset with 1 trillion text tokens and 3.4 billion images, a 10x scale-up from existing open-source datasets. Additionally, we include previously untapped sources such as PDFs and ArXiv papers. 🍃 MINT-1T is designed to facilitate research in multimodal pretraining. 🍃 MINT-1T is created by a team from the University of Washington in… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/MINT-1T-PDF-CC-2023-06.
Dataset Card for "winogrande" Dataset Summary WinoGrande is a new collection of 44k problems, inspired by Winograd Schema Challenge (Levesque, Davis, and Morgenstern 2011), but adjusted to improve the scale and robustness against the dataset-specific bias. Formulated as a fill-in-a-blank task with binary options, the goal is to choose the right option for a given sentence which requires commonsense reasoning. Supported Tasks and Leaderboards More Information… See the full description on the dataset page: https://huggingface.co/datasets/allenai/winogrande.
About this dataset Context The datasets provided include the players data for the Career Mode from FIFA 15 to FIFA 23. The data allows multiple comparisons for the same players across the last 9 versions of the video game. Some ideas of possible analysis: Historical comparison between Messi and Ronaldo (what skill attributes changed the most during time - compared to real-life stats); Ideal budget to create a competitive team (at the level of top n teams in Europe) and… See the full description on the dataset page: https://huggingface.co/datasets/jsulz/FIFA23.