Model Hub
Browse PQC-verified AI models, datasets, and tools
GPIC: A Giant Permissive Image Corpus for Visual Generation Keshigeyan Chandrasegaran*1, Kyle Sargent*1, Suchir Agarwal1, Michael Jang1, Michael Poli1,2, Juan Carlos Niebles1,4, Justin Johnson3, Jiajun Wu1, Li Fei-Fei1 1 Stanford University 2 Radical Numerics 3 University of Michigan 4 Salesforce… See the full description on the dataset page: https://huggingface.co/datasets/stanford-vision-lab/gpic.
SAGE-10k SAGE-10k is a large-scale interactive indoor scene dataset featuring realistic layouts, generated by the agentic-driven pipeline introduced in "SAGE: Scalable Agentic 3D Scene Generation for Embodied AI". The dataset contains 10,000 diverse scenes spanning 50 room types and styles, along with 565K uniquely generated 3D objects. 🔑 Key Features SAGE-10k integrates a wide variety of scenes, and particularly, preserves small items for… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/SAGE-10k.
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 The version in this repository concatenated all the configs in the original dataset and then shuffled them. This is done to facilitate streaming the data directly from the hub! Load… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceM4/FineVisionMax.
LLaVA-OneVision-2-Data Training data for the LLaVA-OneVision-2 multimodal model family, covering large-scale video and spatial reasoning corpora used in mid-training. Dataset Composition Subset Format Description mid_training_video/60s_rest/ WebDataset (.tar) 10,809 shards of ~60s video clips mid_training_video/caption_v0/split_30s.jsonl JSONL Captions for 30-second video clips mid_training_video/caption_v0/split_60s.jsonl JSONL Captions for… See the full description on the dataset page: https://huggingface.co/datasets/mvp-lab/LLaVA-OneVision-2-Data.
Vietnamese Cultural VQA Dataset is a comprehensive multimodal dataset focusing on Vietnamese cultural heritage. It contains 28,505 images across 12 cultural categories with 119,012 question-answer pairs in Vietnamese and English. The dataset covers diverse aspects of Vietnamese culture including architecture, cuisine, traditional clothing, landscapes, festivals, folk culture, traditional games, sports, handicrafts, musical instruments, daily life, and transportation.
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.
Dataset Card for "trivia_qa" Dataset Summary TriviaqQA is a reading comprehension dataset containing over 650K question-answer-evidence triples. TriviaqQA includes 95K question-answer pairs authored by trivia enthusiasts and independently gathered evidence documents, six per question on average, that provide high quality distant supervision for answering the questions. Supported Tasks and Leaderboards More Information Needed Languages… See the full description on the dataset page: https://huggingface.co/datasets/mandarjoshi/trivia_qa.
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.
CREST forcing (parquet) EF5/CREST hourly forcing for CONUS, 2016-present, packed as one tar per variable/year. dir variable source cadence mrms/ precipitation MRMS QPE (corrected) hourly temp/ 2 m temperature NLDAS-2 FORA hourly pet/ potential ET FEWS NET daily PET daily Each *.tar expands to individual .pqf (Apache Arrow parquet) grids readable by the EF5 v4.5 native parquet reader. Used by the Space vincewin/CREST_AI. Download + extract one year, e.g.: from… See the full description on the dataset page: https://huggingface.co/datasets/vincewin/CREST_data.
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.