Datasets
Training datasets with quantum-safe provenance
Summary This is the dataset proposed in our paper [ICLR 2025] OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation. OpenVid-1M is a high-quality text-to-video dataset designed for research institutions to enhance video quality, featuring high aesthetics, clarity, and resolution. It can be used for direct training or as a quality tuning complement to other video datasets. All videos in the OpenVid-1M dataset have resolutions of at least 512×512.… See the full description on the dataset page: https://huggingface.co/datasets/nkp37/OpenVid-1M.
OpenMathInstruct-2 OpenMathInstruct-2 is a math instruction tuning dataset with 14M problem-solution pairs generated using the Llama3.1-405B-Instruct model. The training set problems of GSM8K and MATH are used for constructing the dataset in the following ways: Solution augmentation: Generating chain-of-thought solutions for training set problems in GSM8K and MATH. Problem-Solution augmentation: Generating new problems, followed by solutions for these new problems.… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/OpenMathInstruct-2.
MMMU (A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI) 🌐 Homepage | 🏆 Leaderboard | 🤗 Dataset | 🤗 Paper | 📖 arXiv | GitHub 🔔News 🛠️[2026-04-21]: Fixed option issue in test_Psychology_15. ‼️[2026-02-12]: We have released the answers for the test set! You can now evaluate your models on the test set locally! 🎉 🛠️[2024-05-30]: Fixed duplicate option issues in Materials dataset items (validation_Materials_25;… See the full description on the dataset page: https://huggingface.co/datasets/MMMU/MMMU.
NU-TONIC raw SFT Full Satellite imagery and aligned land-cover outputs packaged as image–text rows for fine-tuning in SFT format. JSONL user prompts name the modality (satellite imagery vs. overhead context) where it matters. Provenance Locations: GeoGuessr-style POIs (source: stochastic/random_streetview_images_pano_v0.0.2) Optical: Sentinel-2 multispectral optical COGs from a public STAC catalog, blue/green/red or visual preview, percentile-stretched to uint8. Labels:… See the full description on the dataset page: https://huggingface.co/datasets/PEBE691445/sat-image-boundingbox-sft-full.
Dataset Card for MNIST Dataset Summary The MNIST dataset consists of 70,000 28x28 black-and-white images of handwritten digits extracted from two NIST databases. There are 60,000 images in the training dataset and 10,000 images in the validation dataset, one class per digit so a total of 10 classes, with 7,000 images (6,000 train images and 1,000 test images) per class. Half of the image were drawn by Census Bureau employees and the other half by high school students… See the full description on the dataset page: https://huggingface.co/datasets/ylecun/mnist.
Dataset Card for PAWS: Paraphrase Adversaries from Word Scrambling Dataset Summary PAWS: Paraphrase Adversaries from Word Scrambling This dataset contains 108,463 human-labeled and 656k noisily labeled pairs that feature the importance of modeling structure, context, and word order information for the problem of paraphrase identification. The dataset has two subsets, one based on Wikipedia and the other one based on the Quora Question Pairs (QQP) dataset. For further… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/paws.
GroundCUA: Grounding Computer Use Agents on Human Demonstrations 🌐 Website | 📑 Paper | 🤗 Dataset | 🤖 Models GroundCUA Dataset GroundCUA is a large and diverse dataset of real UI screenshots paired with structured annotations for building multimodal computer use agents. It covers 87 software platforms across productivity tools, browsers, creative tools, communication apps, development environments, and system utilities. GroundCUA is designed for research on GUI… See the full description on the dataset page: https://huggingface.co/datasets/ServiceNow/GroundCUA.
Dataset Card for "sciq" Dataset Summary The SciQ dataset contains 13,679 crowdsourced science exam questions about Physics, Chemistry and Biology, among others. The questions are in multiple-choice format with 4 answer options each. For the majority of the questions, an additional paragraph with supporting evidence for the correct answer is provided. Supported Tasks and Leaderboards More Information Needed Languages More Information Needed… See the full description on the dataset page: https://huggingface.co/datasets/allenai/sciq.
GUI-360°: A Comprehensive Dataset And Benchmark For Computer-Using Agents Paper | Code GUI-360° is a large-scale, comprehensive dataset and benchmark suite designed to advance Computer-Using Agents (CUAs). 🎯 Key Features 🔢 1.2M+ executed action steps across thousands of trajectories 💼 Popular Windows office applications (Word, Excel, PowerPoint) 📸 Full-resolution screenshots with accessibility metadata 🎨 Multi-modal trajectories with reasoning traces ✅ Both… See the full description on the dataset page: https://huggingface.co/datasets/vyokky/GUI-360.
TOFU: Task of Fictitious Unlearning 🍢 The TOFU dataset serves as a benchmark for evaluating unlearning performance of large language models on realistic tasks. The dataset comprises question-answer pairs based on autobiographies of 200 different authors that do not exist and are completely fictitiously generated by the GPT-4 model. The goal of the task is to unlearn a fine-tuned model on various fractions of the forget set. Quick Links Website: The landing page for TOFU… See the full description on the dataset page: https://huggingface.co/datasets/locuslab/TOFU.
⚠️ Important: If you have already submitted an access request but have not completed the required DocuSign agreement, your request will remain pending. Please complete signing and we will grant access once verified. Interactive Intelligence from Human Xperience Xperience-10M Dataset Summary Xperience-10M is a large-scale egocentric multimodal dataset of human experience for embodied AI, robotics, world models, and spatial… See the full description on the dataset page: https://huggingface.co/datasets/ropedia-ai/xperience-10m.
🍃 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-2023-50.
Dataset Card for truthful_qa Dataset Summary TruthfulQA is a benchmark to measure whether a language model is truthful in generating answers to questions. The benchmark comprises 817 questions that span 38 categories, including health, law, finance and politics. Questions are crafted so that some humans would answer falsely due to a false belief or misconception. To perform well, models must avoid generating false answers learned from imitating human texts.… See the full description on the dataset page: https://huggingface.co/datasets/truthfulqa/truthful_qa.
Dataset Card for GPQA GPQA is a multiple-choice, Q&A dataset of very hard questions written and validated by experts in biology, physics, and chemistry. When attempting questions out of their own domain (e.g., a physicist answers a chemistry question), these experts get only 34% accuracy, despite spending >30m with full access to Google. We request that you do not reveal examples from this dataset in plain text or images online, to reduce the risk of leakage into foundation model… See the full description on the dataset page: https://huggingface.co/datasets/Idavidrein/gpqa.
🚀 AutoMathText-V2: A 2.46 Trillion Token AI-Curated STEM Pretraining Dataset 🎉 AutoMathText-v2 has surpassed 1.5 million downloads! We'd love to know how you're using it. Please take 1 minute to fill out our use case survey. Your feedback will directly shape the future roadmap of this dataset.👉 Share your use case here 📊 AutoMathText-V2 consists of 2.46 trillion tokens of high-quality, deduplicated text spanning web content, mathematics, code, reasoning, and… See the full description on the dataset page: https://huggingface.co/datasets/OpenSQZ/AutoMathText-V2.