Datasets

Boasting over 10,000 hours of cumulative data and 1 million+ clips, it ranks as the largest open-source embodied intelligence dataset in the industry. Compared with other datasets, it has the following advantages: Ample Data Volume & Strong Generalization Each skill is supported by sufficient data, collected from over 3,000 households and nearly 10,000 distinct fine-grained targets. It avoids simple repetitions and ensures robust generalization. Authentic Scenarios & Focused… See the full description on the dataset page: https://huggingface.co/datasets/ad1t7a/10Kh-RealOmin-OpenData.

15T token dataset of cleaned English web data. Deduplicated and filtered from CommonCrawl, outperforms C4 and RefinedWeb for LLM pretraining.

PrimeBot Household Bimanual Manipulation Challenge Dataset 中文 | English 中文 目录 关于我们 更新日志 真机遥操作数据 训练集说明 验证集说明 数据集字段说明 URDF 图像 语言指令 本体感知与动作 机器人推理接口 UMI数据 数据概览 目录结构 数据集字段说明 图像 本体感知与动作 索引字段 标注与 IMU 关于我们 我们来自上纬新材-启元研究院，我们的使命是加速个人机器人时代到来，加速家用机器人时代到来。我们开源高质量面向家庭操作的双臂操作数据集，同时开放机器人硬件描述以供可视化、可复现研究。 如果本数据集对您的工作有帮助，感谢引用： @misc{xu2026scalingbimanualhouseholdmanipulation, title={Scaling Bimanual Household Manipulation from 1,500… See the full description on the dataset page: https://huggingface.co/datasets/challenge-2026/challenge_data.

Dataset Card for CIFAR-10 Dataset Summary The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images. The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the remaining images in random order, but some training batches may contain… See the full description on the dataset page: https://huggingface.co/datasets/uoft-cs/cifar10.

MulSeT: A Benchmark for Multi-view Spatial Understanding Tasks Paper: Why Do MLLMs Struggle with Spatial Understanding? A Systematic Analysis from Data to Architecture Code: https://github.com/WanyueZhang-ai/spatial-understanding A high-level overview of the MulSeT benchmark. The dataset challenges models to integrate information from two distinct viewpoints of a 3D scene to answer spatial reasoning questions. 📝 Dataset Summary MulSeT is a comprehensive benchmark… See the full description on the dataset page: https://huggingface.co/datasets/WanyueZhang/MulSeT.

Forecast News Deduplicated daily news corpus used by forecast-sim and future-sim. Snapshot 31,696,086 articles 3,401 daily partitions Coverage: 2016-08-26 through 2026-06-30 Snapshot published: 2026-07-13 Stored data size: approximately 168.8 GB The Parquet files are the canonical complete representation. The repository also contains daily JSONL files where available and compact headline JSON files used by article-browsing workflows. Layout Files… See the full description on the dataset page: https://huggingface.co/datasets/shash42/forecast-news.

ERA5 Based on Hersbach et al. 2020 with data exposed through Copernicus C3S API 26 variable subset of data as described in Table 3 of Bonev et al. 2023. Each file contains all 26 variables sampled every 6 hours (starting with 00:00:00) for an entire month in a given year.

Gen-HumanEgo 1,800+ hours of egocentric human demonstrations with synchronized, structured supervision for embodied AI and robot learning. Gen-HumanEgo contains real-world first-person demonstrations collected across diverse tasks, people, environments, and ways of performing activities using a unified six-camera DAS-Ego setup. GenRobot's Data Foundation Model (DFM) processes the recordings to provide complementary training signals for human motion, spatial understanding… See the full description on the dataset page: https://huggingface.co/datasets/genrobot2025/Gen-HumanEgo.

Arena Leaderboard Dataset Historical snapshots of the Arena leaderboard. Usage from datasets import load_dataset # Load all historical text style control data ds = load_dataset("lmarena-ai/leaderboard-dataset", "text_style_control", split="full") # Load the current text style control leaderboard ds = load_dataset("lmarena-ai/leaderboard-dataset", "text_style_control", split="latest") # Filter to overall category ds =… See the full description on the dataset page: https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset.

Complete Wikipedia dump across all languages. Standard pretraining data source. Structured articles with metadata.

RW-RL Dataset: Real-World Reinforcement Learning for Robots Human-intervention companion dataset: RW-RL-HIL-Dataset (BodenAI) is a separately hosted release of real-world policy rollouts and human corrections. Download it from its own dataset page. RW-RL Dataset is a real-world robot interaction dataset released by Boden Intelligence, Junpu Innovation Center, and the MINT Lab at Shanghai Jiao Tong University. It is designed for a bottleneck that… See the full description on the dataset page: https://huggingface.co/datasets/MINT-SJTU/RW-RL-Dataset.

DartLab Data Structured company data from DART & EDGAR disclosure filings DART 전자공시 + EDGAR 공시 데이터 — 한국 2,700사 / 미국 970사 What is this? Pre-collected Parquet files from DartLab — a Python library that turns DART (Korea) and EDGAR (US) disclosure filings into one structured company map. 한국 DART 전자공시 시스템과 미국 SEC EDGAR에서 수집한 기업 공시 데이터입니다. This dataset is the data layer behind DartLab. When you run dartlab.Company("005930"), the library automatically downloads the… See the full description on the dataset page: https://huggingface.co/datasets/eddmpython/dartlab-data.

WorldBench WorldBench is a new benchmark designed to evaluate the physical understanding and prediction of modern world models and vision-language models. There are two components: Video based: This is a benchmark designed to evaluate video-to-video world foundation models such as Cosmos. It consists of videos 132 frames long of 425 simulated scenes with RGB, Normals, Depth, Flow, and Segmentations. Text based: This is a subset which adds text-based questions to 181 videos… See the full description on the dataset page: https://huggingface.co/datasets/worldbenchmark/IntuitivePhysics.

Locus Commit Pool v1 Native Git history, preserved as replayable software changes Commit message · complete selected before-state · unified patches · native object IDs · provenance · experimental labels Locus Commit Pool v1 is a large evidence pool for studying and training on how real software changes. Each document represents one surviving single-parent, multi-file Git commit. It keeps the commit message, the selected files as they existed before the… See the full description on the dataset page: https://huggingface.co/datasets/ahnaftaz/locus-commit-pool-v1.

Dataset Card for "jat-dataset-tokenized" More Information needed

SynData 中文说明 Demo If the video cannot be displayed in your environment, open it directly: assets/syndata-demo.mp4 1. Overview SynData is a next-generation large-scale real-world multimodal dataset newly released by PsiBot. It comprehensively covers key dimensions including vision, language, and action, and provides highly realistic, high-density, and highly usable human data as a solid foundation for embodied intelligence training. Powered by… See the full description on the dataset page: https://huggingface.co/datasets/PsiBotAI/SynData.

Dataset Card for "hellaswag" Dataset Summary HellaSwag: Can a Machine Really Finish Your Sentence? is a new dataset for commonsense NLI. A paper was published at ACL2019. Supported Tasks and Leaderboards More Information Needed Languages More Information Needed Dataset Structure Data Instances default Size of downloaded dataset files: 71.49 MB Size of the generated dataset: 65.32 MB Total amount of disk used: 136.81… See the full description on the dataset page: https://huggingface.co/datasets/Rowan/hellaswag.

WorldCode Exported JSON Field Specification The following specification is based on the actual outputs produced by the export script, as well as the example file worldcode_HS-2-1420125020208_2025-10-21-14-50-09_3_s0_vlta_reorg_sample_1-2.json. Top-level Fields Field Description worldcode_name Name of the current sample, typically also the filename of the exported JSON. dataset_path Absolute path to the original worldcode directory. task_description… See the full description on the dataset page: https://huggingface.co/datasets/tars-robotics/WIYH.

3DCodeVerse — Towards Building the Universe via Code 3DCodeVerse aims to gather any code that creates, renders, or governs 3D — every dialect, one corpus. Text / Image / Video ↔ 3D Code ↔ 3D Assets Every entry is a self-contained, runnable project: the code, its rendered outputs, a metadata card, and text captions. Domains in scope: Object Modeling · Scene & World Modeling · Rendering · Materials & Shaders · Physics & Simulation · Animation & Articulation. 📄 Paper:… See the full description on the dataset page: https://huggingface.co/datasets/ilabai/3dcodeverse.

Dataset Card for The Cauldron Dataset description The Cauldron is part of the Idefics2 release. It is a massive collection of 50 vision-language datasets (training sets only) that were used for the fine-tuning of the vision-language model Idefics2. Load the dataset To load the dataset, install the library datasets with pip install datasets. Then, from datasets import load_dataset ds = load_dataset("HuggingFaceM4/the_cauldron", "ai2d") to download and load the… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceM4/the_cauldron.