datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
DatasetWithCapitalLettersMuSR
MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning
Creating murder mysteries that require multi-step reasoning with commonsense using ChatGPT!
By: Zayne Sprague, Xi Ye, Kaj Bostrom, Swarat Chaudhuri, and Greg Durrett.
View the dataset on our custom viewer and project website!
Check out the paper. Appeared at ICLR 2024 as a spotlight presentation!
Git Repo with the source data, how to recreate the dataset (and create new ones!) here
us_election_2024_telegram_distilled
A billion Telegram messages about the 2024 US presidential election
This is a dataset of Telegram messages collected during the 2024 US presidential election. For more details, see https://dl.acm.org/doi/10.1145/3701716.3715297.
~1.03B messages, ~43K chats, ~0.8TB (distilled).
~350M English messages have toxicity- and hate-related scores from the Perspective API. For more details, see https://support.perspectiveapi.com/s/about-the-api-attributes-and-languages?language=en_US.
~350M… See the full description on the dataset page: https://huggingface.co/datasets/leonardoblas/us_election_2024_telegram_distilled.TexasPokerRobot
TexasPokerRobot
TexasPokerRobot is a robot manipulation dataset collected in a Texas poker tabletop environment. The raw episodes are stored as compressed NumPy .npz files, organized by action folder. This release adds a Hugging Face-compatible manifest at data/train.csv so the dataset has a standard loadable split and a working Dataset Viewer while preserving the original raw episode files.
Dataset Summary
1,470 raw episode files
14 action folders, with 105 episodes per… See the full description on the dataset page: https://huggingface.co/datasets/Winniechen2002/TexasPokerRobot.tiny-shakespeare
Data source
Downloaded via Andrej Karpathy's nanogpt repo from this link
Data Format
The entire dataset is split into train (90%) and test (10%).
All rows are at most 1024 tokens, using the Llama 2 tokenizer.
All rows are split cleanly so that sentences are whole and unbroken.
jigsaw-toxic-comment-classification-challenge
Dataset Description
You are provided with a large number of Wikipedia comments which have been labeled by human raters for toxic behavior. The types of toxicity are:
toxic
severe_toxic
obscene
threat
insult
identity_hate
You must create a model which predicts a probability of each type of toxicity for each comment.
File descriptions
train.csv - the training set, contains comments with their binary labels
test.csv - the test set, you must predict the toxicity… See the full description on the dataset page: https://huggingface.co/datasets/thesofakillers/jigsaw-toxic-comment-classification-challenge.trex-visualizer
T-Rex Dataset Visualizer
A browseable subset of the T-Rex dataset — Tactile-Rich Bimanual Dexterous
Manipulation — collected on a bimanual Dexmate Vega-1 robot equipped with
two Sharpa Wave dexterous hands.
This visualizer subset contains 3,838 short trajectory clips drawn from the
full 100-hour T-Rex collection, organized by (verb, object, hand) so you can
quickly inspect coverage across motion primitives and object categories.
For the full dataset (multi-view RGB, robot… See the full description on the dataset page: https://huggingface.co/datasets/Beakerman0101/trex-visualizer.tmmluplus
TMMLU+ : Large scale traditional chinese massive multitask language understanding
iKala presents TMMLU+, a large-scale benchmark for evaluating LLM capabilities in Traditional Chinese, with content primarily reflecting Taiwan's linguistic, educational, and professional contexts. It covers 66 subjects, from elementary to professional domains, and is approximately six times larger than TMMLU with broader, more balanced coverage.
TMMLU+ v1.1 improves benchmark quality through… See the full description on the dataset page: https://huggingface.co/datasets/ikala/tmmluplus.THEMol
THEMol: Torsion, Hessian, Energy of Molecules
Dataset Summary
THEMol is an open-source collection of quantum mechanical properties tailored for organic molecules. It provides large-scale density functional theory (DFT) data for exploring intramolecular potential energy surfaces, including optimized geometries, structural relaxation trajectories, torsion scans, constrained torsion relaxation trajectories, Hessian matrices, and MBIS-derived atomic properties.
The dataset… See the full description on the dataset page: https://huggingface.co/datasets/ByteDance-Seed/THEMol.Embodied-Captioning
Embodied Image Captioning – Manually Annotated Test Set
Paper: Embodied Image Captioning: Self-supervised Learning Agents for Spatially Coherent Image Descriptions (ICCV 2025)Authors: Tommaso Galliena, Tommaso Apicella, Stefano Rosa, Pietro Morerio, Alessio Del Bue, Lorenzo NataleAffiliations: Italian Institute of Technology (IIT), University of GenoaProject Website: https://hsp-iit.github.io/embodied-captioningCode: https://github.com/hsp-iit/embodied-captioning
📦… See the full description on the dataset page: https://huggingface.co/datasets/TommyBsk/Embodied-Captioning.toxic-chat
Update
[01/31/2024] We update the OpenAI Moderation API results for ToxicChat (0124) based on their updated moderation model on on Jan 25, 2024.[01/28/2024] We release an official T5-Large model trained on ToxicChat (toxicchat0124). Go and check it for you baseline comparision![01/19/2024] We have a new version of ToxicChat (toxicchat0124)!
Content
This dataset contains toxicity annotations on 10K user prompts collected from the Vicuna online demo.
We utilize a human-AI… See the full description on the dataset page: https://huggingface.co/datasets/lmsys/toxic-chat.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.Mixamo-Animations-Characters
Mixamo Animations and Characters
A complete snapshot of the Mixamo library: 2,317 motion clips and
114 rigged characters, exported as binary FBX (FBX 7.7 / fbx7_2019) with per-file metadata.
All animations share one uniform 65-joint mixamorig skeleton, so any clip can drive any
compatible character without remapping.
Use animation_motion/ and character_refined/. The full export contains 2,446 animation
files, but 129 are single-pose assets that carry no motion (Mixamo's *_Pose*… See the full description on the dataset page: https://huggingface.co/datasets/tanish434/Mixamo-Animations-Characters.discover-tools2025-challenge-task-instancesVPData
VideoPainter
This repository contains the implementation of the paper "VideoPainter: Any-length Video Inpainting and Editing with Plug-and-Play Context Control"
Keywords: Video Inpainting, Video Editing, Video Generation
Yuxuan Bian12, Zhaoyang Zhang1‡, Xuan Ju2, Mingdeng Cao3, Liangbin Xie4, Ying Shan1, Qiang Xu2✉
1ARC Lab, Tencent PCG 2The Chinese University of Hong Kong 3The University of Tokyo 4University of Macau ‡Project Lead ✉Corresponding Author
Your… See the full description on the dataset page: https://huggingface.co/datasets/TencentARC/VPData.Synthetic-UAV-Flight-Trajectories
UAV Trajectory Dataset
Summary
This dataset comprises over 5000 random UAV (Unmanned Aerial Vehicle) trajectories collected over 20 hours of flight time. It is intended for training AI models such as trajectory prediction applications. The dataset is generated through an automated pipeline for the creation and preprocessing of UAV synthetic trajectories, making it ready for direct AI model training.
Data Description
The dataset features parameterized… See the full description on the dataset page: https://huggingface.co/datasets/riotu-lab/Synthetic-UAV-Flight-Trajectories.taxbench-au
TaxBench-AU
A benchmark for testing whether AI agents can calculate Australian tax.
TaxBench-AU contains 156 Australian tax calculation questions, presented as multiple-choice (4-option) worked tax problems. The benchmark is designed to test whether an AI agent can read the facts, apply the right Australian tax rule for the relevant income year, do the calculation, and choose the correct answer.
The Kaggle mirror is published as Agent Tax Exam for Australian Tax.
Paper:… See the full description on the dataset page: https://huggingface.co/datasets/Pn101/taxbench-au.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.takedown-notices
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twitter-financial-news-sentiment
Dataset Description
The Twitter Financial News dataset is an English-language dataset containing an annotated corpus of finance-related tweets. This dataset is used to classify finance-related tweets for their sentiment.
The dataset holds 11,932 documents annotated with 3 labels:
sentiments = {
"LABEL_0": "Bearish",
"LABEL_1": "Bullish",
"LABEL_2": "Neutral"
}
The data was collected using the Twitter API. The current dataset supports the multi-class classification… See the full description on the dataset page: https://huggingface.co/datasets/zeroshot/twitter-financial-news-sentiment.TruthfulQA
Dataset Card for TruthfulQA
Dataset Summary
TruthfulQA: Measuring How Models Mimic Human Falsehoods
We propose a benchmark to measure whether a language model is truthful in generating answers to questions. The benchmark comprises 817 questions that span 38 categories, including health, law, finance and politics. We crafted questions that some humans would answer falsely due to a false belief or misconception. To perform well, models must avoid generating false answers… See the full description on the dataset page: https://huggingface.co/datasets/domenicrosati/TruthfulQA.webvid-10MTACK_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.MIntRec
Dataset details
In real-world conversational interactions, we usually combine information from multiple modalities (e.g., text, video, audio) to help analyze human intentions. Though intent analysis has been widely explored in the Natural Language Processing community, there is a scarcity of data for multimodal intent analysis. Thus, we provide a novel multimodal intent benchmark dataset, MIntRec, to boom the research. To the best of our knowledge, it is the first multimodal intent… See the full description on the dataset page: https://huggingface.co/datasets/THU-IAR/MIntRec.customer-support-tickets
Featuring Labeled Customer Emails and Support Responses
🔧 Synthetic IT Ticket Generator — Custom Dataset
Create a dataset tailored to your own queues & priorities (no PII).
👉 Generate custom data
Define your queues, priorities, language
Need an on-prem AI to auto-classify tickets?→ Open Ticket AI
There are 2 Versions of the dataset, the new version has more tickets, but only languages english and german. So please look at both files, to find what best fits… See the full description on the dataset page: https://huggingface.co/datasets/Tobi-Bueck/customer-support-tickets.mmlu_pro_leaderboard_submissionTravelPlanner
TravelPlanner Dataset
TravelPlanner is a benchmark crafted for evaluating language agents in tool-use and complex planning within multiple constraints. (See our paper for more details.)
Introduction
In TravelPlanner, for a given query, language agents are expected to formulate a comprehensive plan that includes transportation, daily meals, attractions, and accommodation for each day.
TravelPlanner comprises 1,225 queries in total. The number of days and hard constraints… See the full description on the dataset page: https://huggingface.co/datasets/osunlp/TravelPlanner.Truebones-ZOO-Annotations
Truebones ZOO Annotations
Text prompts, per-clip metadata, rest-pose renders and the exact build pipeline for
Truebones ZOO — 1,097 animal motion clips across 74 skeletons: mammals, birds,
reptiles, insects, marine and prehistoric creatures. 1.02 hours, 111,158 frames, uniformly
30 fps. Rigs range from 9 to 143 joints; clips from 0.3 to 18.5 seconds.
The motion files themselves are not in this repository. Truebones ZOO is a commercial
library by Truebones Motions Animation… See the full description on the dataset page: https://huggingface.co/datasets/tanish434/Truebones-ZOO-Annotations.arabic-stem-lexicon
Arabic Diacritized-Stem Lexicon
An undiacritized Arabic surface form → its most frequent diacritized stem.
Standard Arabic writes no short vowels, so anything that has to pronounce Arabic
must first put them back. A neural diacritizer does that well on rare words, where
inference is the only thing there is. On common words it is the wrong tool:
which vowels كتاب carries is not a thing to be inferred, it is a thing to be looked
up — and models get exactly these wrong, reading… See the full description on the dataset page: https://huggingface.co/datasets/TigreGotico/arabic-stem-lexicon.