Datasets

Dataset Card for "winogrande" Dataset Summary WinoGrande is a new collection of 44k problems, inspired by Winograd Schema Challenge (Levesque, Davis, and Morgenstern 2011), but adjusted to improve the scale and robustness against the dataset-specific bias. Formulated as a fill-in-a-blank task with binary options, the goal is to choose the right option for a given sentence which requires commonsense reasoning. Supported Tasks and Leaderboards More Information… See the full description on the dataset page: https://huggingface.co/datasets/allenai/winogrande.

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.

Dataset Card for IFEval Dataset Summary This dataset contains the prompts used in the Instruction-Following Eval (IFEval) benchmark for large language models. It contains around 500 "verifiable instructions" such as "write in more than 400 words" and "mention the keyword of AI at least 3 times" which can be verified by heuristics. To load the dataset, run: from datasets import load_dataset ifeval = load_dataset("google/IFEval") Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/google/IFEval.

Boasting over 13,000 hours of cumulative data and 5 million+ clips, it ranks as the largest open-source embodied intelligence dataset in the industry. Update Notes：Stage 3 data upload completed. 13,000+ hours of pure dual-hand data with frame-level alignment latency < 1ms Full high-precision trajectory reconstruction, breaking the limit of superficial open source, fully ready-to-use 3,000+ contributors and 10,000+ real household scenarios with exceptional diversity Comprehensive… See the full description on the dataset page: https://huggingface.co/datasets/genrobot2025/10Kh-RealOmin-OpenData.

SAGE-10k SAGE-10k is a large-scale interactive indoor scene dataset featuring realistic layouts, generated by the agentic-driven pipeline introduced in "SAGE: Scalable Agentic 3D Scene Generation for Embodied AI". The dataset contains 10,000 diverse scenes spanning 50 room types and styles, along with 565K uniquely generated 3D objects. 🔑 Key Features SAGE-10k integrates a wide variety of scenes, and particularly, preserves small items for… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/SAGE-10k.

Dataset Card for "sciq" Dataset Summary The SciQ dataset contains 13,679 crowdsourced science exam questions about Physics, Chemistry and Biology, among others. The questions are in multiple-choice format with 4 answer options each. For the majority of the questions, an additional paragraph with supporting evidence for the correct answer is provided. Supported Tasks and Leaderboards More Information Needed Languages More Information Needed… See the full description on the dataset page: https://huggingface.co/datasets/allenai/sciq.

Dataset Card for OpenAI HumanEval Dataset Summary The HumanEval dataset released by OpenAI includes 164 programming problems with a function sig- nature, docstring, body, and several unit tests. They were handwritten to ensure not to be included in the training set of code generation models. Supported Tasks and Leaderboards Languages The programming problems are written in Python and contain English natural text in comments and docstrings.… See the full description on the dataset page: https://huggingface.co/datasets/openai/openai_humaneval.

ABC-130k ABC-130k is the largest open-source robot teleoperation dataset. It contains bimanual manipulation trajectories collected on two-arm YAM stations. Episodes are distributed as MCAP files, with subtask annotations kept as separate artifacts so they can be revised or extended independently of the underlying episode data. For details on the accompanying paper, see abc.bot. Please see the GitHub repo here for code to train and deploy with this dataset. Dataset… See the full description on the dataset page: https://huggingface.co/datasets/XDOF/ABC-130k.

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.

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.

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.

ngii-map-full-light Light point/line extract from NGII 1/1000 topographic data for Korea. Not for shipping into GitHub — use this Hugging Face dataset instead. CRS Korea_2000_Central_Belt_2010 projected meters [x, y] Layers (per region under by_region/<region>/) Layer Description C023 poles (전주/통신주) C022 lights (가로등·보안등) A002 roads (도로 중심선) B001_tiny building footprints <25 m² as centroids B002 lines (구분/재질 라인) Also:… See the full description on the dataset page: https://huggingface.co/datasets/SKPark1/ngii-map-full-light.

Dataset Card for NuminaMath CoT Dataset Summary Approximately 860k math problems, where each solution is formatted in a Chain of Thought (CoT) manner. The sources of the dataset range from Chinese high school math exercises to US and international mathematics olympiad competition problems. The data were primarily collected from online exam paper PDFs and mathematics discussion forums. The processing steps include (a) OCR from the original PDFs, (b) segmentation… See the full description on the dataset page: https://huggingface.co/datasets/AI-MO/NuminaMath-CoT.

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

GPIC: A Giant Permissive Image Corpus for Visual Generation Keshigeyan&nbsp;Chandrasegaran*1,&nbsp; Kyle&nbsp;Sargent*1,&nbsp; Suchir&nbsp;Agarwal1,&nbsp; Michael&nbsp;Jang1,&nbsp; Michael&nbsp;Poli1,2,&nbsp; Juan&nbsp;Carlos&nbsp;Niebles1,4,&nbsp; Justin&nbsp;Johnson3,&nbsp; Jiajun&nbsp;Wu1,&nbsp; Li&nbsp;Fei-Fei1 1&nbsp;Stanford University&nbsp;&nbsp; 2&nbsp;Radical Numerics&nbsp;&nbsp; 3&nbsp;University of Michigan&nbsp;&nbsp; 4&nbsp;Salesforce… See the full description on the dataset page: https://huggingface.co/datasets/stanford-vision-lab/gpic.

AgiBot World 2026 Real-World Embodied Intelligence Dataset Overview As robotics research advances into real-world scenarios, the demand for authentic, high-quality data has become increasingly urgent. Following AGIBOT WORLD's "ImageNet moment," we now release the AGIBOT WORLD 2026 dataset. Built upon massive real-world scenes, it systematically spans pivotal research directions in embodied intelligence, designed to power the next generation of… See the full description on the dataset page: https://huggingface.co/datasets/agibot-world/AgiBotWorld2026.

Dataset Card for SQuAD Dataset Summary Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable. SQuAD 1.1 contains 100,000+ question-answer pairs on 500+ articles. Supported Tasks and Leaderboards Question Answering.… See the full description on the dataset page: https://huggingface.co/datasets/rajpurkar/squad.

Introduction Welcome to MLAAD: The Multi-Language Audio Anti-Spoofing Dataset -- a dataset to train, test and evaluate audio deepfake detection. See the paper for more information. License MLAAD is published strictly for non-commercial academic research use, under the CC-BY-NC 4.0 license. Commercial use is not permitted. Download the dataset Option 1: Hugging Face datasets library Install the datasets package: pip install… See the full description on the dataset page: https://huggingface.co/datasets/mueller91/MLAAD.