Model Hub

Browse PQC-verified AI models, datasets, and tools

ServiceNow/GroundCUA HF Unverified

GroundCUA: Grounding Computer Use Agents on Human Demonstrations 🌐 Website | šŸ“‘ Paper | šŸ¤— Dataset | šŸ¤– 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.

Task_categories:image-To-TextLanguage:enSize_categories:1M<n<10MModality:imageComputer_useAgents
Idavidrein/gpqa HF Unverified

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.

Benchmark:officialBenchmark:eval-YamlTask_categories:question-AnsweringTask_categories:text-GenerationLanguage:enSize_categories:1K<n<10K
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facebook/vjepa2-vith-fpc64-256 HF Unverified

Video-ClassificationTransformersSafetensorsVjepa2Feature ExtractionVideo HIGH
nvidia/OpenMathInstruct-2 HF Unverified

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.

Task_categories:question-AnsweringTask_categories:text-GenerationLanguage:enSize_categories:10M<n<100MFormat:parquetModality:text
mvp-lab/LLaVA-OneVision-1.5-Instruct-Data HF Unverified

LLaVA-OneVision-1.5 Instruction Data Paper | Code šŸ“Œ Introduction This dataset, LLaVA-OneVision-1.5-Instruct, was collected and integrated during the development of LLaVA-OneVision-1.5. LLaVA-OneVision-1.5 is a novel family of Large Multimodal Models (LMMs) that achieve state-of-the-art performance with significantly reduced computational and financial costs. This meticulously curated 22M instruction dataset (LLaVA-OneVision-1.5-Instruct) is part of a comprehensive and… See the full description on the dataset page: https://huggingface.co/datasets/mvp-lab/LLaVA-OneVision-1.5-Instruct-Data.

Task_categories:image-Text-To-TextLanguage:enSize_categories:10M<n<100MModality:imageModality:textMultimodal
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facebook/vjepa2-vitg-fpc64-256 HF Unverified

Video-ClassificationTransformersSafetensorsVjepa2Feature ExtractionVideo HIGH
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MCG-NJU/videomae-base-finetuned-kinetics HF Unverified

Video-ClassificationTransformersPyTorchSafetensorsVideomaeVision MEDIUM
nvidia/PhysicalAI-Robotics-GR00T-Teleop-GR1 HF Unverified

Introduction TL;DR: DreamDojo is a generalist robot world model pretrained on 44k hours of human egocentric data, showing unprecedented generalization to diverse objects and environments. Project page: https://dreamdojo-world.github.io/ Paper: https://arxiv.org/abs/2602.06949 Code: https://github.com/NVIDIA/DreamDojo How to Use Check out https://github.com/NVIDIA/DreamDojo Citation @article{gao2026dreamdojo, title={DreamDojo: A Generalist Robot… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/PhysicalAI-Robotics-GR00T-Teleop-GR1.

Size_categories:1M<n<10MFormat:parquetModality:tabularModality:videoLibrary:datasetsLibrary:dask
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KingTechnician/videomae-small-finetuned-kinetics-xd-violence-binary HF PQC Verified

Video-ClassificationTransformersSafetensorsVideomaeGenerated_from_trainerBase_model:MCG-NJU/videomae-Small-Finetuned-Kinetics MEDIUM
cornell-movie-review-data/rotten_tomatoes HF Unverified

Dataset Card for "rotten_tomatoes" Dataset Summary Movie Review Dataset. This is a dataset of containing 5,331 positive and 5,331 negative processed sentences from Rotten Tomatoes movie reviews. This data was first used in Bo Pang and Lillian Lee, ``Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales.'', Proceedings of the ACL, 2005. Supported Tasks and Leaderboards More Information Needed Languages… See the full description on the dataset page: https://huggingface.co/datasets/cornell-movie-review-data/rotten_tomatoes.

Task_categories:text-ClassificationTask_ids:sentiment-ClassificationAnnotations_creators:crowdsourcedLanguage_creators:crowdsourcedMultilinguality:monolingualSource_datasets:original
nvidia/OpenMathReasoning HF Unverified

OpenMathReasoning OpenMathReasoning is a large-scale math reasoning dataset for training large language models (LLMs). This dataset contains 306K unique mathematical problems sourced from AoPS forums with: 3.2M long chain-of-thought (CoT) solutions 1.7M long tool-integrated reasoning (TIR) solutions 566K samples that select the most promising solution out of many candidates (GenSelect) Additional 193K problems sourced from AoPS forums (problems only, no solutions) We used… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/OpenMathReasoning.

Task_categories:question-AnsweringTask_categories:text-GenerationLanguage:enSize_categories:1M<n<10MFormat:parquetModality:text
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google/vivit-b-16x2 HF Unverified

Video-ClassificationTransformersPyTorchVivitVision MEDIUM
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nvidia/GR00T-N1.7-3B HF Unverified

RoboticsSafetensorsGr00tN1d7 HIGH
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nvidia/Alpamayo-1.5-10B HF Unverified

RoboticsSafetensorsAlpamayo1_5Base_model:nvidia/Cosmos-Reason2-8BBase_model:finetune:nvidia/Cosmos-Reason2-8BEnglish HIGH
saffatgazi/fish-vista HF Unverified

Dataset Card for Fish-Visual Trait Analysis (Fish-Vista) Note that the '</Use this dataset>' option will only load the CSV files. To download the entire dataset, including all processed images and segmentation annotations, refer to Instructions for downloading dataset and images. See Example Code to Use the Segmentation Dataset Figure 1. A schematic representation of the different tasks in Fish-Vista Dataset. Instructions for downloading dataset… See the full description on the dataset page: https://huggingface.co/datasets/saffatgazi/fish-vista.

Task_categories:image-ClassificationTask_categories:image-SegmentationLanguage:enSize_categories:10K<n<100KFormat:csvModality:image
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MCG-NJU/videomae-large HF Unverified

Video-ClassificationTransformersPyTorchSafetensorsVideomaePretraining MEDIUM
imageomics/fish-vista HF Unverified

Dataset Card for Fish-Visual Trait Analysis (Fish-Vista) Note that the '</Use this dataset>' option will only load the CSV files. To download the entire dataset, including all processed images and segmentation annotations, refer to Instructions for downloading dataset and images. See Example Code to Use the Segmentation Dataset Figure 1. A schematic representation of the different tasks in Fish-Vista Dataset. Instructions for downloading dataset and images… See the full description on the dataset page: https://huggingface.co/datasets/imageomics/fish-vista.

Task_categories:image-ClassificationTask_categories:image-SegmentationLanguage:enSize_categories:10K<n<100KFormat:csvModality:image
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OpenGVLab/VideoMAEv2-Huge HF Unverified

Video-ClassificationSafetensorsVideoMAEv2_BaseVisionCustom_code MEDIUM
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google/vivit-b-16x2-kinetics400 HF Unverified

Video-ClassificationTransformersPyTorchVivitVision MEDIUM
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facebook/vjepa2-vitl-fpc16-256-ssv2 HF Unverified

Video-ClassificationTransformersSafetensorsVjepa2VideoBase_model:facebook/vjepa2-Vitl-Fpc64-256 MEDIUM
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