datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
drlc-leaderboard-dataDatasetWithCapitalLettersCADS-dataset
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Overview
CADS is a robust, fully automated framework for segmenting 167 anatomical structures in Computed Tomography (CT), spanning from head to knee regions across diverse anatomical systems.
The framework consists of two main components:
CADS-dataset:
22,022 CT volumes with complete annotations for 167 anatomical structures.
Most extensive whole-body CT dataset… See the full description on the dataset page: https://huggingface.co/datasets/huggingface/CADS-dataset.dataset-with-standalone-yamlThis is a test dataset used in the datasets library CI
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.data_jobs
🧠 data_jobs Dataset
A dataset of real-world data analytics job postings from 2023, collected and processed by Luke Barousse.
Background
I've been collecting data on data job postings since 2022. I've been using a bot to scrape the data from Google, which come from a variety of sources.
You can find the full dataset at my app datanerd.tech.
Serpapi has kindly supported my work by providing me access to their API. Tell them I sent you and get 20% off paid plans.… See the full description on the dataset page: https://huggingface.co/datasets/lukebarousse/data_jobs.officeqa
OfficeQA
Dataset Summary
OfficeQA is a grounded reasoning benchmark by Databricks for evaluating model and agent performance on end-to-end reasoning over real-world documents.
The benchmark consists of question–answer pairs that require reasoning over historical U.S. Treasury Bulletin documents (1939–2025), which contain dense financial tables, charts, and narrative text. OfficeQA is designed to test retrieval, tool use, and multi-step reasoning in… See the full description on the dataset page: https://huggingface.co/datasets/databricks/officeqa.Bitext-customer-support-llm-chatbot-training-dataset
Bitext - Customer Service Tagged Training Dataset for LLM-based Virtual Assistants
Overview
This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the Customer Support sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-customer-support-llm-chatbot-training-dataset.Obstacle-Detection-Dataset-YOLO
ROD-Dataset: Real-Time Obstacle Detection for Smartphone-Based Assistive Vision
24,326-image, 25-class YOLO dataset for obstacle detection
This dataset is the data product of our Real-Time Obstacle Detection (ROD) project at Amirkabir University of Technology, Tehran. The project addresses two related public-safety problems on the city sidewalk: the limited situational awareness of people living with visual impairments, and the elevated collision and fall risk for pedestrians… See the full description on the dataset page: https://huggingface.co/datasets/Abtinzandi/Obstacle-Detection-Dataset-YOLO.eccv2026-cad-challenge-data
ECCV 2026 CAD Challenge Data
This challenge is part of the workshop The Path to Manufacturing: Evolving
3D Generation to Intelligent Computer-Aided Design.
Workshop homepage: https://3dgen-cad-workshop.github.io/
Challenge submission Space: https://huggingface.co/spaces/jingwei-xu-00/eccv2026-cad-challenge
Dataset rendering and preparation code (only .step files are required): https://github.com/DavidXu-JJ/eccv2026-cad-challenge-data-render
This repository contains the public… See the full description on the dataset page: https://huggingface.co/datasets/jingwei-xu-00/eccv2026-cad-challenge-data.CADS-dataset
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Overview
CADS is a robust, fully automated framework for segmenting 167 anatomical structures in Computed Tomography (CT), spanning from head to knee regions across diverse anatomical systems.
The framework consists of two main components:
CADS-dataset:
22,022 CT volumes with complete annotations for 167 anatomical structures.
Most extensive whole-body CT dataset… See the full description on the dataset page: https://huggingface.co/datasets/sunghong/CADS-dataset.spotify-tracks-dataset
Content
This is a dataset of Spotify tracks over a range of 125 different genres. Each track has some audio features associated with it. The data is in CSV format which is tabular and can be loaded quickly.
Usage
The dataset can be used for:
Building a Recommendation System based on some user input or preference
Classification purposes based on audio features and available genres
Any other application that you can think of. Feel free to discuss!
Column… See the full description on the dataset page: https://huggingface.co/datasets/maharshipandya/spotify-tracks-dataset.task_data
QuantCodeEval
A benchmark for evaluating LLM coding agents on quantitative-strategy code
reproduction from finance research papers.
Status: Anonymous artifact for the 30-task benchmark.
Release mirrors
The release is mirrored at two anonymous locations:
Hugging Face Datasets — complete anonymous release:
https://huggingface.co/datasets/quantcodeeval/task_data
anonymous.4open.science — browseable mirror:
https://anonymous.4open.science/r/QuantCodeEval-Anonymous… See the full description on the dataset page: https://huggingface.co/datasets/quantcodeeval/task_data.Tunisian-Proverbs-with-Image-Associations-A-Cultural-and-Linguistic-DatasetTunisian Proverbs with Image Associations: A Cultural and Linguistic Dataset
Description
This dataset explores the rich oral tradition of Tunisian proverbs mapped into text format, pairing each with contextual explanations, English translations both word-to-word and it's equivalent Target Language dynamic, Automated prompt and AI-generated visual interpretations.
It bridges linguistic, cultural, and visual modalities making it valuable for tasks in cross-cultural NLP, generative… See the full description on the dataset page: https://huggingface.co/datasets/HabibaAbderrahim/Tunisian-Proverbs-with-Image-Associations-A-Cultural-and-Linguistic-Dataset.hnm-fashion-recommendations-data
Dataset Rekomendasi Fashion H&M
Dataset ini berisi data transaksi, atribut pelanggan, dan metadata produk yang telah dianonimkan dari H&M Group. Kumpulan data komprehensif ini memungkinkan pemodelan perilaku pembelian pelanggan secara mendalam.
Wawasan yang dihasilkan dapat dimanfaatkan untuk berbagai tujuan bisnis yang strategis, mulai dari meningkatkan personalisasi pengalaman berbelanja, mengoptimalkan manajemen inventaris untuk efisiensi produksi, hingga mendukung inisiatif… See the full description on the dataset page: https://huggingface.co/datasets/einrafh/hnm-fashion-recommendations-data.TACK_Tunnel_Data
TACK Tunnel Data (TTD): A Benchmark Dataset for Deep Learning-Based Defect Detection in Tunnels
Tunnels are essential elements of transportation infrastructure, but are increasingly affected by ageing and deterioration mechanisms such as cracking. Regular inspections are required to ensure their safety, yet traditional manual procedures are time-consuming, subjective, and costly. Recent advances in mobile mapping systems and Deep Learning (DL) enable automated visual inspections.… See the full description on the dataset page: https://huggingface.co/datasets/TACK-project/TACK_Tunnel_Data.sim-datasets
SIM-Datasets: A Unified Symbolic Regression Benchmark
A standardized benchmark collection designed for the Scientific Intelligent Modelling (SIM) toolkit, providing comprehensive datasets for symbolic regression research and applications.
Overview
SIM-Datasets serves as a unified benchmark for symbolic regression tasks, offering standardized datasets with consistent formatting and evaluation protocols. This collection is specifically curated to support the Scientific… See the full description on the dataset page: https://huggingface.co/datasets/scientific-intelligent-modelling/sim-datasets.suno-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.officeqa-pro-v2
OfficeQA Pro v2
Dataset Summary
OfficeQA Pro v2 is a grounded reasoning benchmark by Databricks for evaluating model and agent performance on end-to-end reasoning over real-world documents.
The benchmark consists of question–answer pairs that require reasoning over two centuries of U.S. Federal Accounts of Receipts and Expenditures reporting (1793–2024) — Combined Statements of Receipts, Outlays, and Balances of the United States Government, together with earlier… See the full description on the dataset page: https://huggingface.co/datasets/databricks/officeqa-pro-v2.linkedin_job_listingsDataset-GB1-fitness
Description
This dataset contains fitness score of mutant GB1 protein.
Protein Format: AA sequence
Splits
traing: 119644
valid: 14917
test: 14800
Related paper
Nicholas C Wu, Lei Dai, C Anders Olson, James O Lloyd-Smith, Ren Sun (2016) Adaptation in protein fitness landscapes is facilitated by indirect paths eLife 5:e16965
https://doi.org/10.7554/eLife.16965
Label
Label is the fitness of mutant protein. The fitness of each variant can be viewed as… See the full description on the dataset page: https://huggingface.co/datasets/SaProtHub/Dataset-GB1-fitness.stock-market-data-warehousedoc-formats-csv-1
[doc] formats - csv - 1
This dataset contains one csv file at the root:
data.csv
kind,sound
dog,woof
cat,meow
pokemon,pika
human,hello
The YAML section of the README does not contain anything related to loading the data (only the size category metadata):
---
size_categories:
- n<1K
---
SpatialLM-Dataset
SpatialLM Dataset
The SpatialLM dataset is a large-scale, high-quality synthetic dataset designed by professional 3D designers and used for real-world production. It contains point clouds from 12,328 diverse indoor scenes comprising 54,778 rooms, each paired with rich ground-truth 3D annotations. SpatialLM dataset provides an additional valuable resource for advancing research in indoor scene understanding, 3D perception, and… See the full description on the dataset page: https://huggingface.co/datasets/manycore-research/SpatialLM-Dataset.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.pending-medicare-provider-enrollment-data
Pending Medicare Provider Enrollment Data
This is a dated, source-receipted sample of behavioral-health NPIs newly present in CMS's pending first-time Medicare enrollment files on 2026-07-13, compared with the immediately prior 2026-07-09 publication.
Pending does not mean approved. A row indicates that a first-time Medicare enrollment application appeared in a CMS pending file. It does not prove enrollment, credentialing, licensure, a new practice, service availability… See the full description on the dataset page: https://huggingface.co/datasets/unitedideas/pending-medicare-provider-enrollment-data.L-FAME
L-FAME: Longitudinal Focused Attention Meditation EEG Dataset and Benchmark
A longitudinal 64-channel EEG dataset and benchmark for studying focused attention meditation (FAM) and how its neural signatures evolve across a six-week training period. 74 healthy adults were recorded at a pre-intervention baseline; 44 of them returned for a post-intervention follow-up. Three FAM techniques are systematically compared: Hare Krishna mantra (HK), SA-TA-NA-MA mantra (SA), and Breath… See the full description on the dataset page: https://huggingface.co/datasets/L-FAME-Dataset-Benchmark/L-FAME.booksummaries_cleanedCifer-Fraud-Detection-Dataset-AF
📊 Cifer Fraud Detection Dataset
🧠 Overview
The Cifer-Fraud-Detection-Dataset-AF is a high-fidelity, fully synthetic dataset created to support the development and benchmarking of privacy-preserving, federated, and decentralized machine learning systems in financial fraud detection.
This dataset draws structural inspiration from the PaySim simulator, which was built using aggregated mobile money transaction data from a real financial provider operating in 14+ countries.… See the full description on the dataset page: https://huggingface.co/datasets/CiferAI/Cifer-Fraud-Detection-Dataset-AF.protein_data_testsplit 1, 2 -> for sequences
split 3, 4 -> for residues