Model Hub

ColliderML: Dataset Release 1 Dataset Description This dataset contains simulated high-energy physics collision events generated using the Open Data Detector (ODD) geometry within the Key4hep and ACTS (A Common Tracking Software) frameworks, representing a generic collider detector similar to those at the HL-LHC. Dataset Summary Collision Energy: 14 TeV (proton-proton) Detector: Open Data Detector (ODD) Simulation: DD4hep + Geant4 + ACTS Format: Apache Parquet… See the full description on the dataset page: https://huggingface.co/datasets/CERN/ColliderML-Release-1.

ニコニコ実況 過去ログアーカイブ ニコニコ実況 過去ログアーカイブは、ニコニコ実況 のサービス開始から現在までのすべての過去ログコメントを収集したデータセットです。 去る2020年12月、ニコニコ実況は ニコニコ生放送内の一公式チャンネルとしてリニューアル されました。これに伴い、2009年11月から運用されてきた旧システムは提供終了となり（事実上のサービス終了）、torne や BRAVIA などの家電への対応が軒並み終了する中、当時の生の声が詰まった約11年分の過去ログも同時に失われることとなってしまいました。 そこで 5ch の DTV 板の住民が中心となり、旧ニコニコ実況が終了するまでに11年分の全チャンネルの過去ログをアーカイブする計画が立ち上がりました。紆余曲折あり Nekopanda 氏が約11年分のラジオや BS も含めた全チャンネルの過去ログを完璧に取得してくださったおかげで、11年分の過去ログが電子の海に消えていく事態は回避できました。しかし、旧 API が廃止されてしまったため過去ログを API… See the full description on the dataset page: https://huggingface.co/datasets/echodict/KakologArchives_duplicate.

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.

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.

Typed Digital Signatures Dataset This comprehensive dataset contains synthetic digital signatures rendered across 30 different Google Fonts, specifically selected for their handwriting and signature-style characteristics. Each font contributes unique stylistic elements, making this dataset ideal for robust signature analysis and font recognition tasks. Dataset Overview Total Fonts: 30 different Google Fonts Images per Font: 3,000 signatures Total Dataset Size: ~90,000… See the full description on the dataset page: https://huggingface.co/datasets/Benjy/typed_digital_signatures.

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.

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

REPID: Rendering Evaluation of Photographic Image Dataset REPID (officially introduced as the Rendering Evaluation of Photographic Image Dataset) is a large-scale benchmark designed for Image Rendering Quality Assessment (IRQA). Unlike traditional Image Quality Assessment (IQA) which focuses on technical degradations like noise or blur, REPID aims to model subjective human aesthetic preferences for different rendering styles of the same scene. Dataset Overview… See the full description on the dataset page: https://huggingface.co/datasets/vsevolodpl/REPID.

Dataset Card for Street View House Numbers Dataset Summary SVHN is a real-world image dataset for developing machine learning and object recognition algorithms with minimal requirement on data preprocessing and formatting. It can be seen as similar in flavor to MNIST (e.g., the images are of small cropped digits), but incorporates an order of magnitude more labeled data (over 600,000 digit images) and comes from a significantly harder, unsolved, real world problem… See the full description on the dataset page: https://huggingface.co/datasets/ufldl-stanford/svhn.

Tomato Leaves Dataset Overview This dataset contains images of tomato leaves categorized into different classes based on the type of disease or health condition. The dataset is divided into training, validation, and test sets, with a ratio of 8:1:1. The classes include various diseases as well as healthy leaves. The dataset includes both augmented and non-augmented images. Dataset Structure The dataset is organized into three main splits: train validation test… See the full description on the dataset page: https://huggingface.co/datasets/codraja2006/tomato-leaves-dataset.

Agentic Critic Dataset High-quality AIGC images with rich metadata for aesthetic evaluation. Metadata Fields Each entry in metadata.jsonl contains: prompt: Positive prompt negative_prompt: Negative prompt model: Model name and hash sampler: Sampling method steps: Generation steps cfg_scale: CFG scale seed: Random seed stats: Engagement metrics image_path: Relative path to image Usage from datasets import load_dataset dataset =… See the full description on the dataset page: https://huggingface.co/datasets/ChengyouJia/agentic-critic-dataset.

Military Aircraft Detection & Classification Dataset 88 Classes with Advanced Background Suppression Overview This dataset is a professionally curated resource for training high-performance object detection and image classification models such as YOLOv11.It contains 88 distinct military aircraft classes and is explicitly designed for real-world deployment, where false positives from civilian aircraft, birds, and small drones are common. To address this, the… See the full description on the dataset page: https://huggingface.co/datasets/Ahnuf/Military_Aircraft_Detection_Classification_Image_Dataset.

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.