Model Hub
Browse PQC-verified AI models, datasets, and tools
Dataset Card for "imdb" Dataset Summary Large Movie Review Dataset. This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training, and 25,000 for testing. There is additional unlabeled data for use as well. Supported Tasks and Leaderboards More Information Needed Languages More Information Needed Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/stanfordnlp/imdb.
FineWeb-HQ Dataset Summary FineWeb-HQ is a high-quality, model-filtered pretraining dataset derived as a subset of FineWeb. FineWeb-HQ was created by selecting the top 10% of FineWeb documents based on a deep learning classifier trained to identify structured and knowledge-rich samples. This classifier uses XLM-RoBERTa embeddings to score documents. To validate our approach, we pretrained 1B-parameter LLM models with a Llama-like architecture across multiple languages and… See the full description on the dataset page: https://huggingface.co/datasets/epfml/FineWeb-HQ.
🍃 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-2024-18.
MADLAD-400 Dataset and Introduction MADLAD-400 (Multilingual Audited Dataset: Low-resource And Document-level) is a document-level multilingual dataset based on Common Crawl, covering 419 languages in total. This uses all snapshots of CommonCrawl available as of August 1, 2022. The primary advantage of this dataset over similar datasets is that it is more multilingual (419 languages), it is audited and more highly filtered, and it is document-level. The main disadvantage… See the full description on the dataset page: https://huggingface.co/datasets/allenai/MADLAD-400.
Dataset Card for MATH-500 This dataset contains a subset of 500 problems from the MATH benchmark that OpenAI created in their Let's Verify Step by Step paper. See their GitHub repo for the source file: https://github.com/openai/prm800k/tree/main?tab=readme-ov-file#math-splits
MMLU-Pro Dataset MMLU-Pro dataset is a more robust and challenging massive multi-task understanding dataset tailored to more rigorously benchmark large language models' capabilities. This dataset contains 12K complex questions across various disciplines. |Github | 🏆Leaderboard | 📖Paper | 🚀 What's New [2026.03.11] Added more cutting-edge frontier models to the leaderboard, including the Claude-4.6 series, Seed2.0 series, Qwen3.5 series, and Gemini-3.1-Pro, among… See the full description on the dataset page: https://huggingface.co/datasets/TIGER-Lab/MMLU-Pro.
🍃 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-2023-23.
GIFT-Eval Pre-training Datasets Pretraining dataset aligned with GIFT-Eval that has 71 univariate and 17 multivariate datasets, spanning seven domains and 13 frequencies, totaling 4.5 million time series and 230 billion data points. Notably this collection of data has no leakage issue with the train/test split and can be used to pretrain foundation models that can be fairly evaluated on GIFT-Eval. 📄 Paper 🖥️ Code 📔 Blog Post 🏎️ Leader Board Ethical Considerations… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/GiftEvalPretrain.
Dataset Card for "super_glue" Dataset Summary SuperGLUE (https://super.gluebenchmark.com/) is a new benchmark styled after GLUE with a new set of more difficult language understanding tasks, improved resources, and a new public leaderboard. Supported Tasks and Leaderboards More Information Needed Languages More Information Needed Dataset Structure Data Instances axb Size of downloaded dataset files: 0.03 MB Size of… See the full description on the dataset page: https://huggingface.co/datasets/aps/super_glue.
Wikipedia dataset containing cleaned articles of all languages. The datasets are built from the Wikipedia dump (https://dumps.wikimedia.org/) with one split per language. Each example contains the content of one full Wikipedia article with cleaning to strip markdown and unwanted sections (references, etc.).
Dataset Card for OpenBookQA Dataset Summary OpenBookQA aims to promote research in advanced question-answering, probing a deeper understanding of both the topic (with salient facts summarized as an open book, also provided with the dataset) and the language it is expressed in. In particular, it contains questions that require multi-step reasoning, use of additional common and commonsense knowledge, and rich text comprehension. OpenBookQA is a new kind of… See the full description on the dataset page: https://huggingface.co/datasets/allenai/openbookqa.
Nemotron-Pre-Training-Dataset-v1 Release Data Overview This pretraining dataset, for generative AI model training, preserves high-value math and code while enriching it with diverse multilingual Q&A, fueling the next generation of intelligent, globally-capable models. This dataset supports NVIDIA Nemotron Nano 2, a family of large language models (LLMs) that consists of the NVIDIA-Nemotron-Nano-9B-v2, NVIDIA-Nemotron-Nano-9B-v2-Base, and NVIDIA-Nemotron-Nano-12B-v2-Base… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-CC-v2.
Egocentric-100K is the largest dataset of manual labor. You can visualize the dataset here. Egocentric-100K is state-of-the-art in hand visibility and active manipulation density compared to previous in-the-wild egocentric datasets. The complete 30,000 frame evaluation set is available at Egocentric-100K-Evaluation. Dataset Statistics Attribute Value Total Hours 100,405 Total Frames 10.8 billion Video Clips 2,010,759 Median Clip Length 180.0 seconds Mean… See the full description on the dataset page: https://huggingface.co/datasets/builddotai/Egocentric-100K.
Fine Vision FineVision is a massive collection of datasets with 17.3M images, 24.3M samples, 88.9M turns, and 9.5B answer tokens, designed for training state-of-the-art open Vision-Language-Models. More detail can be found in the blog post: https://huggingface.co/spaces/HuggingFaceM4/FineVision Load the data from datasets import load_dataset, get_dataset_config_names # Get all subset names and load the first one available_subsets =… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceM4/FineVision.