datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
tweet_eval
Dataset Card for tweet_eval
Dataset Summary
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. The tasks include - irony, hate, offensive, stance, emoji, emotion, and sentiment. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
Supported Tasks and Leaderboards
text_classification: The dataset can be… See the full description on the dataset page: https://huggingface.co/datasets/cardiffnlp/tweet_eval.stanford_cars
Stanford Cars Dataset
Dataset Overview
Splits:
Training: 8144 images used for model training.
Test: 8041 images used for evaluation.
Contrast: 8041 images with high contrast for robustness testing.
Gaussian Noise: 8041 images corrupted by Gaussian noise for robustness testing.
Impulse Noise: 8041 images corrupted by impulse noise for robustness testing.
JPEG Compression: 8041 compressed images for robustness testing.
Motion Blur: 8041 images with motion blur for… See the full description on the dataset page: https://huggingface.co/datasets/tanganke/stanford_cars.e-CARE
Dataset of (Du et al., 2022) (Unofficial reupload)
Abstract
Understanding causality has vital importance for various Natural Language Processing (NLP) applications. Beyond the labeled instances, conceptual explanations of the causality can provide deep understanding of the causal fact to facilitate the causal reasoning process. However, such explanation information still remains absent in existing causal reasoning resources. In this paper, we fill this gap by presenting… See the full description on the dataset page: https://huggingface.co/datasets/12ml/e-CARE.gspc-hub-cards
GSPC hub cards — mill cards, not board axes
SWIFT census (live): https://councilof.ai/api/swift
XRPL reader (live): https://councilof.ai/api/xrpl
One row per signed measurement card: one model, one axis, one date, Ed25519 over the body. A row is MEASURED only when a signed card verifies. Absent (model, axis) pairs are absent — not zero.
Measurement, not certification. Cards are evidence of bytes on a frozen bank at a time — never approval, rating, or safety guarantee.… See the full description on the dataset page: https://huggingface.co/datasets/csoai/gspc-hub-cards.comprehensive-arithmetic-problems-carriescar-bench-dataset
CAR-Bench Dataset
CAR-Bench is a benchmark for evaluating AI voice assistants in a realistic automotive (car) environment.
It tests an agent's ability to correctly use vehicle control tools, handle disambiguation, and avoid hallucinations.
Dataset Structure
The dataset is organized into task configs and mock data configs:
Tasks
Each task defines a user persona, an instruction, the initial vehicle/environment context, and the ground-truth sequence of tool-call… See the full description on the dataset page: https://huggingface.co/datasets/johanneskirmayr/car-bench-dataset.card_backend
Eval Cards Backend Dataset
Pre-computed evaluation data powering the Eval Cards frontend.
Generated by the eval-cards backend pipeline.
Last generated: 2026-05-05T11:30:42.961096Z
Quick Stats
Stat
Value
Models
5,678
Evaluations (benchmarks)
798
Metric-level evaluations
1321
Source configs processed
52
Benchmark metadata cards
240
File Structure
.
├── README.md # This file
├── manifest.json… See the full description on the dataset page: https://huggingface.co/datasets/evaleval/card_backend.GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset
📖 The Open Distillation Codex
🌌 The Ultimate Open-Source Distillation Dataset — No Skip, Full, with Attack & Defense 🌌
Where 73 open-source minds converge into one unified stream of intelligence
18M+ Distilled Signals · 7,090 Raw GitHub Repositories · 8 Curated Categories · ~76 GB+
"We did not write this dataset. We assembled it.
Every line is an echo — of a model thinking, a coder drafting, a tutor explaining, a repo breathing.
Seventy-three… See the full description on the dataset page: https://huggingface.co/datasets/Carlosaug47/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset.openai_summarize_tldr
Dataset Card for "openai_summarize_tldr"
More Information needed
corpus-carolinaCarolina is an Open Corpus for Linguistics and Artificial Intelligence with a
robust volume of texts of varied typology in contemporary Brazilian Portuguese
(1970-).monorepo
Persona Cartography — artifact monorepo
Artifact store for the paper Persona Cartography: Charting Language Model
Personality Traits in Weight
Space (arXiv:2607.07916). Code:
persona-cartography/persona-cartography.
This is not a load_dataset-able dataset — it is a single shared repo
holding every artifact the paper's pipeline produces: trained LoRA adapters,
their training data, evaluation results, and the figures' source data. The
paper's figure scripts hydrate from the paths… See the full description on the dataset page: https://huggingface.co/datasets/persona-cartography/monorepo.car-dataset-repo-v3AgiBot-g1_box_storage_cardboard_box_a
AgiBot-g1_box_storage_cardboard_box_a
📋 Overview
This dataset uses an extended format based on LeRobot and is fully compatible with LeRobot.
Robot Type: ruantong_a2d
| Codebase Version: v2.1
End-Effector Type: two_finger_gripper
🏠 Scene Types
This dataset covers the following scene types:
home
🤖 Atomic Actions
This dataset includes the following atomic actions:
place
pick
grasp
📊 Dataset Statistics
Metric
Value
Total… See the full description on the dataset page: https://huggingface.co/datasets/RoboCOIN/AgiBot-g1_box_storage_cardboard_box_a.car-dataset-repodatabench
💾🏋️💾 DataBench 💾🏋️💾
New! All the splits from the SemEval competition, including the test set, are now available in this page.
This repository contains the original 80 datasets used for the paper Question Answering over Tabular Data with DataBench:
A Large-Scale Empirical Evaluation of LLMs which appeared in LREC-COLING 2024 and the associated SemEval 2025 Task 8 competition.
Large Language Models (LLMs) are showing emerging abilities, and one of the latest recognized ones is… See the full description on the dataset page: https://huggingface.co/datasets/cardiffnlp/databench.CareQA
CareQA
Dataset Summary
CareQA is a healthcare QA dataset with two versions:
Closed-Ended Version: A multichoice question answering (MCQA) dataset containing 5,621 QA pairs across six categories. Available in English and Spanish.
Open-Ended Version: A free-response dataset derived from the closed version, containing 2,769 QA pairs (English only).
The dataset originates from… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/CareQA.carbon-pretraining-corpus
🧬 Carbon Pretraining Corpus
Description
173M DNA & RNA sequences · 1.1 trillion nucleotides — the DNA pretraining mixture used to train Carbon, a genomic foundation model.
This dataset is a collection of data sources intended for training genomic foundation models, such as Carbon. It contains DNA and RNA sequences spanning eukaryote and prokaryote species.
Across the four main configs it totals 1.1 T DNA base pairs (180B tokens with Carbon's 6-mer tokenizer). A… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceBio/carbon-pretraining-corpus.CarlaOcc
Database_structure
CarlaOcc/
├── CarlaOccV1/
│ ├── calib/
│ │ └── calib.yaml
│ ├── splits/
│ │ ├── test.txt
│ │ ├── train.txt
│ │ └── val.txt
│ ├── SceneMeshes/
│ │ ├── fg_actors/
│ │ ├── fg_actor_occ/
│ │ └── TownXX_Opt/
│ │ ├── bg_actors/
│ │ └── bg_actor_occ/
│ ├── TownXX_Opt_SeqXX/
│ │ ├── poses/
│ │ │ ├── cam_00.txt
│ │ │ └── lidar.txt
│ │ ├── rgb/
│ │ │ ├── image_00/
│ │ │ │ ├── 0000.png… See the full description on the dataset page: https://huggingface.co/datasets/fengyi233/CarlaOcc.openai_summarize_comparisonsSukaSuka-image-dataset
该数据集包含了《末日时在做什么？有没有空？可以来拯救吗？》大部分主要角色角色的图像数据,来源为动漫截图与同人二创。
为方便LoRA模型训练，所有图片尺寸均截为512x640尺寸，相应打标主要由Waifu Diffusion 1.4 Tagger V2自动完成，部分手工调整。
欢迎提交PR补充或修正本数据集！
Alpha：8.21号之后的clone都是放大了两倍的图片，这是为了sdxl做准备，如果你还需要512*640尺寸的数据集，你可以在clone之后，执行下面的命令
git checkout 183e253c4c304fc6c5ef5046f1940712c349c94e
相关数据集的更正作业正在火热的进行中，请期待继续的更新吧~
AgiBot-g1_box_storage_cardboard_box_c
AgiBot-g1_box_storage_cardboard_box_c
📋 Overview
This dataset uses an extended format based on LeRobot and is fully compatible with LeRobot.
Robot Type: ruantong_a2d
| Codebase Version: v2.1
End-Effector Type: two_finger_gripper
🏠 Scene Types
This dataset covers the following scene types:
home
🤖 Atomic Actions
This dataset includes the following atomic actions:
place
pick
grasp
📊 Dataset Statistics
Metric
Value
Total… See the full description on the dataset page: https://huggingface.co/datasets/RoboCOIN/AgiBot-g1_box_storage_cardboard_box_c.IPL-CARLA-dataset
IPL-CARLA-dataset
Autonomous driving semantic segmentation dataset created with CARLA (Cars Learning to Act) simulator.
Dataset information
Images are generated from two different simulated cities. They include different weather (sunny, foggy and rainy) and daytime (morning, day, sunset and night) conditions. It contains 20000 RGB-rendered images and their corresponding ground truth segmented masks. Segmentation ground truth masks have 35 different classes with colors… See the full description on the dataset page: https://huggingface.co/datasets/isp-uv-es/IPL-CARLA-dataset.Q-CARE
Q-CARE Benchmark
Towards Query-Agnostic RAG Evaluation via Query Coverage and Claim Verifiability
Jeonghwan Choi · Taewon Yun · Minjeong Ban · Gyeonghun Sun · Jae-Gil Lee · Hwanjun Song
Korea Advanced Institute of Science and Technology (KAIST) · COLM 2026
📄 Paper · 💻 Code
Q-CARE is a query-agnostic, fully reference-free framework for evaluating
retrieval-augmented generation. It decomposes queries into sub-queries and
answers into atomic claims, then scores retrieval and… See the full description on the dataset page: https://huggingface.co/datasets/DISLab/Q-CARE.Sastra_ID_Cardxauusd-ticks
XAU/USD Tick Data (May 2021 – May 2026)
Five years of tick-by-tick bid/ask quotes for gold against the US dollar (XAU/USD) at millisecond resolution. Suitable for backtesting high-frequency strategies, market-microstructure research, and time-series modeling.
Dataset details
Instrument
XAU/USD (spot gold)
Period
2021-05-24 → 2026-05-24
Granularity
Tick (millisecond timestamps)
Rows
~hundreds of millions
Format
Apache Parquet (Snappy)
Partitioning… See the full description on the dataset page: https://huggingface.co/datasets/CarlosSilva1/xauusd-ticks.autotrain-data-pick_a_card
AutoTrain Dataset for project: pick_a_card
Dataset Description
This dataset has been automatically processed by AutoTrain for project pick_a_card.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"image": "<224x224 RGB PIL image>",
"target": 0
},
{
"image": "<224x224 RGB PIL image>",
"target": 0
}]
Dataset Fields… See the full description on the dataset page: https://huggingface.co/datasets/rwcuffney/autotrain-data-pick_a_card.CareManip
Dataset Card for CareManip (HDF5 Format)
CareManip is a real-world leader-follower robot teleoperation dataset for care-oriented tabletop manipulation. The release contains 15 task categories and 1,500 HDF5 episodes. Each HDF5 file records one complete demonstration trajectory and preserves the original action and robot-state arrays for reproducible use in robot learning research.
Dataset release: v1.0Dataset DOI: To be generated after the final public releaseAssociated paper:… See the full description on the dataset page: https://huggingface.co/datasets/zw1213757576/CareManip.wds_carsCarDD
🚘 CarDD Dataset
CarDD is a novel, public, large-scale dataset specifically designed for vision-based car damage detection and segmentation.
The dataset contains 4,000 high-resolution car damage images with over 9,000 well-annotated instances, making it the largest public dataset of its kind.
The high resolution of the images (average 684,231 pixels) is a key advantage over existing datasets that have a much lower average resolution (50,334 pixels). Higher resolution allows for… See the full description on the dataset page: https://huggingface.co/datasets/harpreetsahota/CarDD.carte-benchmark
CARTE: Pretraining and Transfer for Tabular Learning
This dataset is the tabular-data benchmark used in the CARTE paper (https://arxiv.org/abs/2402.16785)
CARTE is a pretrained model for tabular data by treating each table row as a star graph and training a graph transformer on top of this representation.
It has the particularity of being made of tables with high-cardinality string.
The codes for CARTE can be found at https://github.com/soda-inria/carte
Descriptions… See the full description on the dataset page: https://huggingface.co/datasets/inria-soda/carte-benchmark.