datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
airlens-live
AirLens Live Data
Live data layer for AirLens, an open
air-quality monitoring platform. Updated by scheduled GitHub Actions pipelines.
Layout mirrors the former Supabase Storage buckets:
Path
Content
Cadence
aq-data/current-*-grid.json
Global pollutant grids (PM2.5/PM10/O3/NO2/CO)
hourly
aq-data/timeline/
GEFS-Aerosols PM2.5 frames, -24h..+24h, 3h step
every 3h
aq-data/predictions/grid_latest.json
AOD→PM2.5 model predictions (p10-p90 + DQSS)
every 3h… See the full description on the dataset page: https://huggingface.co/datasets/Robeedau/airlens-live.AIME_1983_2024Disclaimer: This is a Benchmark dataset! Do not using in training!
This is the Benchmark of AIME from year 1983~2023, and 2024(part 2).
Original: https://artofproblemsolving.com/wiki/index.php/AIME_Problems_and_Solutions
2024(part 1) can be find at https://huggingface.co/datasets/AI-MO/aimo-validation-aime.
Citation
@misc {di_zhang_2025,
author = { {Di Zhang} },
title = { AIME_1983_2024 (Revision 6283828) },
year = 2025,
url = {… See the full description on the dataset page: https://huggingface.co/datasets/di-zhang-fdu/AIME_1983_2024.ai-model-popularity
Datamata AI Model Popularity Index
Weekly popularity of the most-downloaded and trending Hugging Face models: trailing downloads, likes, the model's task and its trending rank. One row per model from the most recent weekly snapshot.
Latest snapshot: 2026-09-20
Models in this release: 50
Updated: weekly
Licence: CC BY 4.0 — free to use and adapt, including commercially, with attribution.
Source & methodology: https://www.datamatastudios.com/datasets
Quickstart… See the full description on the dataset page: https://huggingface.co/datasets/datamatastudios/ai-model-popularity.UltraVideo
UltraVideo: High-Quality UHD 4K Video Dataset
🤓 Project | 📑 Paper | 🤗 Hugging Face (UltraVideo Dataset)) | 🤗 Hugging Face (UltraVideo-Long Dataset)) | 🤗 Hugging Face (UltraWan-1K/4K Weights)
UltraVideo: High-Quality UHD Video Dataset with Comprehensive Captions
🎋 Click below image to watch the 4K demo video.
🤓 First open-sourced UHD-4K/8K video datasets with comprehensive structured (10 types) captions.🤓 Native 1K/4K videos generation by UltraWan.… See the full description on the dataset page: https://huggingface.co/datasets/APRIL-AIGC/UltraVideo.multimodal-ct-radiology-reports
Perle AI Multi-phase CECT and CT with Radiology Reports
Summary
A de-identified CT dataset from Perle AI, paired with the original radiology reports. It supports work on multi-modal medical imaging: phase or pathology classification, report generation from images, and visual question answering.
The release has three configurations:
Config
Modality
Subjects
Pairing
cect_3phase
3-phase contrast-enhanced abdominal CT (DICOM)
5
per-subject text report +… See the full description on the dataset page: https://huggingface.co/datasets/Perle-ai/multimodal-ct-radiology-reports.epic-kitchens-100-clips
EPIC-KITCHENS-100 Extracted Clips
About
Dataset of 37455 video clips (24GB) extracted from videos in the EPIC-KITCHENS-100 dataset,
more precisely the extension part not contained in EPIC-KITCHENS-55. For details,
see https://www.lightly.ai/product-updates/epickitchens-100-in-lightlystudio.
The clips folder contains one video for every narration from action annotations stored
in {participant_id}/{narration_id}.mp4. The videos have been downscaled an compressed for easier… See the full description on the dataset page: https://huggingface.co/datasets/lightly-ai/epic-kitchens-100-clips.air-bench-2024
AIRBench 2024
AIRBench 2024 is a AI safety benchmark that aligns with emerging government
regulations and company policies. It consists of diverse, malicious prompts
spanning categories of the regulation-based safety categories in the
AIR 2024 safety taxonomy.
Dataset Details
Dataset Description
AIRBench 2024 is a AI safety benchmark that aligns with emerging government
regulations and company policies. It consists of diverse, malicious prompts
spanning… See the full description on the dataset page: https://huggingface.co/datasets/stanford-crfm/air-bench-2024.aime-1983-2024
AIME Problem Set 1983-2024
Dataset Description
This dataset contains problems from the American Invitational Mathematics Examination (AIME) from 1983 to 2024. The AIME is a prestigious mathematics competition for high school students in the United States and Canada.
Dataset Summary
Source: Kaggle - AIME Problem Set 1983-2024
License: CC0: Public Domain
Total Problems: 2,250
Years Covered: 1983 to 2024
Main Task: Mathematics Problem Solving… See the full description on the dataset page: https://huggingface.co/datasets/gneubig/aime-1983-2024.UltraVideo-Long
UltraVideo: High-Quality UHD 4K Video Dataset
🤓 Project | 📑 Paper | 🤗 Hugging Face (UltraVideo Dataset)) | 🤗 Hugging Face (UltraVideo-Long Dataset)) | 🤗 Hugging Face (UltraWan-1K/4K Weights)
UltraVideo: High-Quality UHD Video Dataset with Comprehensive Captions
🎋 Click below image to watch the 4K demo video.
🤓 First open-sourced UHD-4K/8K video datasets with comprehensive structured (10 types) captions.🤓 Native 1K/4K videos generation by UltraWan.… See the full description on the dataset page: https://huggingface.co/datasets/APRIL-AIGC/UltraVideo-Long.ai-musicarena-human-preference-55kDataset for Kaggle competition on predicting human preference on Chatbot Arena battles.
The training dataset includes over 55,000 real-world user and LLM conversations and user preferences across over 70 state-of-the-art LLMs, such as GPT-4, Claude 2, Llama 2, Gemini, and Mistral models.
Each sample represents a battle consisting of 2 LLMs which answer the same question, with a user label of either prefer model A, prefer model B, tie, or tie (both bad).
Citation
Please cite the… See the full description on the dataset page: https://huggingface.co/datasets/lmarena-ai/arena-human-preference-55k.ECommerce-Women-Clothing-Reviewssuno-ai-music-dataset
Suno AI Music Dataset (Multi-Genre Curated)
A human-curated, multi-genre audio dataset generated with Suno V5.5 (chirp-fenix), covering 100+ sub-sub-genres across electronic, hip-hop, Latin, jazz, world, rock, ambient, pop, reggae, and classical music. Each track ships with full audio (MP3), cover art, the original generation prompt, and a 32-column metadata schema designed for downstream audio-ML research.
This is not a "scrape everything Suno produces" dump. It is a… See the full description on the dataset page: https://huggingface.co/datasets/Kukedlc/suno-ai-music-dataset.cti-bench
Dataset Card for CTIBench
A set of benchmark tasks designed to evaluate large language models (LLMs) on cyber threat intelligence (CTI) tasks.
Dataset Details
Dataset Description
CTIBench is a comprehensive suite of benchmark tasks and datasets designed to evaluate LLMs in the field of CTI.
Components:
CTI-MCQ: A knowledge evaluation dataset with multiple-choice questions to assess the LLMs' understanding of CTI standards, threats, detection strategies… See the full description on the dataset page: https://huggingface.co/datasets/AI4Sec/cti-bench.FINDER_API_KEY_AI_SEARCH_2023
FINDER_API_KEY_AI_SEARCH_2023
tags: data collection, machine learning, API performance
Note: This is an AI-generated dataset so its content may be inaccurate or false
Dataset Description:
The 'FINDER_API_KEY_AI_SEARCH_2023' dataset is designed to collect and analyze data from various AI search engines and their associated API performance metrics. The dataset focuses on the effectiveness of API key-based access in enhancing the search capabilities of AI systems and includes a… See the full description on the dataset page: https://huggingface.co/datasets/infinite-dataset-hub/FINDER_API_KEY_AI_SEARCH_2023.panda-bench
PandaBench
PandaBench is a comprehensive benchmark for evaluating Large Language Model (LLM) safety, focusing on jailbreak attacks, defense mechanisms, and evaluation methodologies.
The PandaGuard framework architecture illustrating the end-to-end pipeline for LLM safety evaluation. The system connects three key components: Attackers, Defenders, and Judges.
Dataset Description
This repository contains the benchmark results from extensive evaluations of various… See the full description on the dataset page: https://huggingface.co/datasets/Beijing-AISI/panda-bench.biasneutral-ajibawa
BIASNEUTRAL Ajibawa
BIASNEUTRAL Ajibawa contains Ajibawa-derived text snippets that passed the GRADIEND bias-neutral filtering pipeline.
It is the Ajibawa-source counterpart to the original aieng-lab/biasneutral dataset, which can not be directly published due to licensing issues.
This dataset provides an easier-to-access solution, while maintaining the same generation principles as the original BIASNEUTRAL properties.
Usage
from datasets import load_dataset
ds… See the full description on the dataset page: https://huggingface.co/datasets/aieng-lab/biasneutral-ajibawa.EchoXFlow
EchoXFlow
This dataset repository contains Croissant metadata plus one uncompressed tar archive per exam.
Extraction
Clone or download the dataset repository first. With Git, this creates an EchoXFlow/ folder:
git lfs install
git clone https://huggingface.co/datasets/Ahus-AIM/EchoXFlow
cd EchoXFlow
The downloaded repository contains croissant.json plus one tar archive per exam under exams/. Extract every exam
archive into a local data/ directory to materialize the… See the full description on the dataset page: https://huggingface.co/datasets/Ahus-AIM/EchoXFlow.mimose_runsphysical-ai-bench-conditional-generation
Physical AI Bench - Conditional Generation
Paper | Code
This dataset (Phsical AI benchmark, PAI-Bench) consisting of 600 examples across three key scenarios: robotic arm operations, driving, and ego-centric everyday life scenes, each representing a critical aspect of Physical AI. This dataset is constructed by sampling a number of videos from three different datasets. The specific details are provided below.
Dataset
Category
Sample Nums
Agibot World
Robotics
200
OpenDV… See the full description on the dataset page: https://huggingface.co/datasets/shi-labs/physical-ai-bench-conditional-generation.MANGO
MANGO: A Corpus of Human Ratings for Speech
MANGO (MUSHRA Assessment corpus using Native listeners and Guidelines to understand human Opinions at scale) is the first large-scale dataset designed for evaluating Text-to-Speech (TTS) systems in Indian languages.
Key Features:
255,150 human ratings of TTS-generated outputs and ground-truth human speech.
Covers two major Indian languages: Hindi & Tamil, and English.
Based on the MUSHRA (Multiple Stimuli with Hidden Reference… See the full description on the dataset page: https://huggingface.co/datasets/ai4bharat/MANGO.finance_agent_benchmark
Finance Agent Benchmark Dataset
We present the Finance Agent Benchmark, featuring challenging and diverse real-world finance research problems which require LLMs to perform complex analysis with the use of of recent SEC filings.
We construct the benchmark using a taxonomy of nine financial task categories, developed in consultation with experts from banks, hedge funds, and private equity firms. The dataset includes 537 expert-authored questions, covering tasks from information… See the full description on the dataset page: https://huggingface.co/datasets/vals-ai/finance_agent_benchmark.i2p
Inaproppriate Image Prompts (I2P)
The I2P benchmark contains real user prompts for generative text2image prompts that are unproportionately likely to produce inappropriate images.
I2P was introduced in the 2023 CVPR paper Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models.
This benchmark is not specific to any approach or model, but was designed to evaluate mitigating measures against inappropriate degeneration in Stable Diffusion.
The corresponding… See the full description on the dataset page: https://huggingface.co/datasets/AIML-TUDA/i2p.CostNav-Teleop-Dataset
CostNav Teleop Dataset
Dataset Summary
The CostNav Teleop Dataset is a large-scale collection of human teleoperation recordings for robot navigation in an urban sidewalk simulation environment. It was collected as part of the CostNav benchmark, which evaluates navigation systems using real-world economic cost and revenue metrics rather than purely technical metrics.
The dataset contains 2,203 teleoperation episodes totaling 50.2 hours of driving… See the full description on the dataset page: https://huggingface.co/datasets/maum-ai/CostNav-Teleop-Dataset.Sujet-Finance-Instruct-177k
Sujet Finance Dataset Overview
The Sujet Finance dataset is a comprehensive collection designed for the fine-tuning of Language Learning Models (LLMs) for specialized tasks in the financial sector. It amalgamates data from 18 distinct datasets hosted on HuggingFace, resulting in a rich repository of 177,597 entries. These entries span across seven key financial LLM tasks, making Sujet Finance a versatile tool for developing and enhancing financial applications of AI.… See the full description on the dataset page: https://huggingface.co/datasets/sujet-ai/Sujet-Finance-Instruct-177k.BPCC
BPCC Dataset
Training
Bharat Parallel Corpus Collection (BPCC) is a comprehensive and publicly available parallel corpus that includes both existing and new data for all 22 scheduled Indic languages. It is comprised of two parts: BPCC-Mined and BPCC-Human, totaling approximately 230 million bitext pairs. BPCC-Mined contains about 228 million pairs, with nearly 126 million pairs newly added as a part of this work. On the other hand, BPCC-Human consists of 2.2 million gold… See the full description on the dataset page: https://huggingface.co/datasets/ai4bharat/BPCC.twitter-airline-sentiment
Dataset Card for Twitter US Airline Sentiment
Dataset Summary
This data originally came from Crowdflower's Data for Everyone library.
As the original source says,
A sentiment analysis job about the problems of each major U.S. airline. Twitter data was scraped from February of 2015 and contributors were asked to first classify positive, negative, and neutral tweets, followed by categorizing negative reasons (such as "late flight" or "rude service").
The data we're… See the full description on the dataset page: https://huggingface.co/datasets/osanseviero/twitter-airline-sentiment.eu-ai-act-article-50-scoreboard
Article 50 historical public-evidence snapshot
This work was produced through an AI-assisted workflow directed by the author. Historical work used Anthropic assistance; the retrospective correction uses OpenAI GPT-6, with separate bounded Gemini advice. All three providers have products in the scored set.
Purpose: provide the corrected paper's version 1.1 bundle under v1_1. Start with its README and correction note. The paper and deposit and GitHub repository identify the same… See the full description on the dataset page: https://huggingface.co/datasets/NMAIResearch/eu-ai-act-article-50-scoreboard.FBI
Finding Blind Spots in Evaluator LLMs with Interpretable Checklists
We present FBI, our novel meta-evaluation framework designed to assess the robustness of evaluator LLMs across diverse tasks and evaluation strategies. Please refer to our paper for more details.
Code
The code to generate the perturbations and run evaluations are available on our github repository: ai4bharat/fbi
Tasks
We manually categorized each prompt into one of the 4 task… See the full description on the dataset page: https://huggingface.co/datasets/ai4bharat/FBI.ai-election-manipulation-cases
AI, Elections and Agency Transfer Evidence Index
Version 0.4.4 · released 21 August 2026 · research cutoff 12 August 2026
The dataset contains 6 documented-manipulation records, not 1,087 cases. Read the counts in this order:
1,087 relational rows -> 64 catalogue entries -> 10 core records
-> 8 incident-eligible records
-> 6 documented-manipulation records
The other two incident-eligible records are transparent contested-use… See the full description on the dataset page: https://huggingface.co/datasets/apol/ai-election-manipulation-cases.