Model Hub

Browse PQC-verified AI models, datasets, and tools

nyu-mll/blimp HF Unverified

Dataset Card for "blimp" Dataset Summary BLiMP is a challenge set for evaluating what language models (LMs) know about major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each containing 1000 minimal pairs isolating specific contrasts in syntax, morphology, or semantics. The data is automatically generated according to expert-crafted grammars. Supported Tasks and Leaderboards More Information Needed Languages More Information… See the full description on the dataset page: https://huggingface.co/datasets/nyu-mll/blimp.

Task_categories:text-ClassificationTask_ids:acceptability-ClassificationAnnotations_creators:crowdsourcedLanguage_creators:machine-GeneratedMultilinguality:monolingualSource_datasets:original
open-index/open-github HF Unverified

OpenGitHub What is it? This dataset contains every public event on GitHub: every push, pull request, issue, star, fork, code review, release, and discussion across all public repositories. GitHub is the world's largest software development platform, home to over 200 million repositories and the daily work of tens of millions of developers, from individual open-source contributors to the engineering teams behind the most widely used software on earth. The archive currently… See the full description on the dataset page: https://huggingface.co/datasets/open-index/open-github.

Task_categories:text-GenerationTask_categories:text-ClassificationTask_categories:feature-ExtractionLanguage:enLanguage:mulSize_categories:100K<n<1M
zai-org/LongBench HF Unverified

LongBench is a comprehensive benchmark for multilingual and multi-task purposes, with the goal to fully measure and evaluate the ability of pre-trained language models to understand long text. This dataset consists of twenty different tasks, covering key long-text application scenarios such as multi-document QA, single-document QA, summarization, few-shot learning, synthetic tasks, and code completion.

Task_categories:question-AnsweringTask_categories:text-GenerationTask_categories:summarizationTask_categories:text-ClassificationLanguage:enLanguage:zh
BrightData/Goodreads-Books HF Unverified

Dataset Card for "BrightData/Goodreads-Books" Dataset Summary Explore a collection of millions of books with the Goodreads dataset, comprising over 6.3M structured records and 14 data fields updated and refreshed regularly. Each entry includes all major data points such as URLs, book IDs, titles, authors, ratings, number of ratings, reviews, summaries, genres, publication dates, author details and prices. For a complete list of data points, please refer to the full "Data… See the full description on the dataset page: https://huggingface.co/datasets/BrightData/Goodreads-Books.

Task_categories:text-ClassificationTask_categories:summarizationTask_categories:text-GenerationLanguage:enSize_categories:1M<n<10MFormat:csv
muset-ai/DeepResearch-Bench-II-Dataset HF Unverified

Task_categories:text-GenerationTask_categories:text-ClassificationLanguage:zhLanguage:enSize_categories:n<1KModality:document
M
MCG-NJU/videomae-base-finetuned-kinetics HF Unverified

Video-ClassificationTransformersPyTorchSafetensorsVideomaeVision MEDIUM
D
distilbert/distilbert-base-uncased-distilled-squad HF Unverified

Question AnsweringTransformersPyTorchTfTfliteCoreml HIGH
Voxel51/Office-Home HF Unverified

Dataset Card for Office-Home This is a FiftyOne dataset with 15588 samples. Installation If you haven't already, install FiftyOne: pip install -U fiftyone Usage import fiftyone as fo import fiftyone.utils.huggingface as fouh # Load the dataset # Note: other available arguments include 'max_samples', etc dataset = fouh.load_from_hub("Voxel51/Office-Home") # Launch the App session = fo.launch_app(dataset) Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/Office-Home.

Task_categories:image-ClassificationLanguage:enSize_categories:10K<n<100KFormat:imagefolderModality:imageLibrary:datasets
T
timpal0l/mdeberta-v3-base-squad2 HF Unverified

Question AnsweringTransformersPyTorchSafetensorsDeberta-V2Deberta HIGH
ceval/ceval-exam HF Unverified

C-Eval is a comprehensive Chinese evaluation suite for foundation models. It consists of 13948 multi-choice questions spanning 52 diverse disciplines and four difficulty levels. Please visit our website and GitHub or check our paper for more details. Each subject consists of three splits: dev, val, and test. The dev set per subject consists of five exemplars with explanations for few-shot evaluation. The val set is intended to be used for hyperparameter tuning. And the test set is for model… See the full description on the dataset page: https://huggingface.co/datasets/ceval/ceval-exam.

Task_categories:text-ClassificationTask_categories:multiple-ChoiceTask_categories:question-AnsweringLanguage:zhSize_categories:10K<n<100KFormat:parquet
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
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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
G
google-bert/bert-large-uncased-whole-word-masking-finetuned-squad HF Unverified

Question AnsweringTransformersPyTorchTfJAXSafetensors HIGH
L
lerobot/smolvla_base HF Unverified

RoboticsLerobotSafetensorsVision-Language-ActionImitation-LearningEnglish MEDIUM
ethz/food101 HF Unverified

Dataset Card for Food-101 Dataset Summary This dataset consists of 101 food categories, with 101'000 images. For each class, 250 manually reviewed test images are provided as well as 750 training images. On purpose, the training images were not cleaned, and thus still contain some amount of noise. This comes mostly in the form of intense colors and sometimes wrong labels. All images were rescaled to have a maximum side length of 512 pixels. Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/ethz/food101.

Task_categories:image-ClassificationTask_ids:multi-Class-Image-ClassificationAnnotations_creators:crowdsourcedLanguage_creators:crowdsourcedMultilinguality:monolingualSource_datasets:extended|other-Foodspotting
Forithmus/MR-RATE HF Unverified

MR-RATE: A Vision-Language Foundation Model and Dataset for Magnetic Resonance Imaging Welcome to the official page for MR-RATE, a pioneering vision-language model and 3D medical imaging dataset that pairs textual reports with brain and spine MRI volumes. Following the approach of CT-RATE, the first 3D medical imaging dataset to pair images with textual reports, MR-RATE offers brain and spine MRI volumes matched with… See the full description on the dataset page: https://huggingface.co/datasets/Forithmus/MR-RATE.

Task_categories:image-To-TextTask_categories:text-To-ImageTask_categories:image-ClassificationTask_categories:question-AnsweringTask_categories:visual-Question-AnsweringTask_categories:zero-Shot-Classification
Horama/animal-200 HF Unverified

Horama/animal-200 Raw wildlife image collection covering 199 species (mammals, birds, reptiles), scraped from multiple web sources. Images are organized by species folder and can be used as-is for image classification (species identification) or as input for downstream annotation pipelines (object detection, etc.). For animal detection, see Horama/animal-200-detection dataset. Sources Images were collected from three web sources using dedicated scrapers: Source… See the full description on the dataset page: https://huggingface.co/datasets/Horama/animal-200.

Task_categories:image-ClassificationTask_categories:object-DetectionLanguage:enLanguage:frSize_categories:10K<n<100KModality:image
zeroMN/hanlp_date-zh HF Unverified

-- 2nd International Chinese Word Segmentation Bakeoff - Data Release Release 1, 2005-11-18 Introduction This directory contains the training, test, and gold-standard data used in the 2nd International Chinese Word Segmentation Bakeoff. Also included is the script used to score the results submitted by the bakeoff participants and the simple segmenter used to generate the baseline and topline data. File List gold/ Contains the gold standard… See the full description on the dataset page: https://huggingface.co/datasets/zeroMN/hanlp_date-zh.

Task_categories:text-ClassificationLanguage:zhSize_categories:100M<n<1BCode
rezzzq/RSCD-1million HF Unverified

RSCD: Road Surface Condition Dataset Dataset Description The Road Surface Condition Dataset (RSCD) is a large-scale image dataset containing over 1 million images for road surface condition classification. This dataset is designed for training computer vision models to identify and classify various road surface types, moisture conditions, and damage severity levels. Dataset Summary Total Images: ~1,028,000 images Image Format: JPG Use Cases: Road condition… See the full description on the dataset page: https://huggingface.co/datasets/rezzzq/RSCD-1million.

Task_categories:image-ClassificationSize_categories:1M<n<10MRoad-ConditionSurface-ClassificationComputer-VisionAutonomous-Driving
a2015003713/military-aircraft-detection-dataset HF Unverified

Military Aircraft Detection Dataset Military aircraft detection dataset in COCO and YOLO format. This dataset is synchronized from the original Kaggle dataset:https://www.kaggle.com/datasets/a2015003713/militaryaircraftdetectiondataset

Task_categories:object-DetectionTask_categories:image-ClassificationTask_categories:image-Feature-ExtractionSize_categories:10K<n<100KFormat:textModality:image
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