Datasets

Picbreeder-VLM Archive Every image evolved by the swarm of vision-language-model "breeders" in In Search of the Ingredients of Open-Endedness: Replicating Picbreeder with Large Vision-Language Models (GECCO 2026), together with the CPPN genomes that produced them, the agents' reasoning transcripts, the lineage graphs, and the analysis artifacts behind the paper and blog. The original Picbreeder (Secretan et al., 2008) let crowds of humans collaboratively evolve images from CPPN… See the full description on the dataset page: https://huggingface.co/datasets/picbreeder-vlm/picbreeder-vlm-archive.

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.

FineWeb-HQ Dataset Summary FineWeb-HQ is a high-quality, model-filtered pretraining dataset derived as a subset of FineWeb. FineWeb-HQ was created by selecting the top 10% of FineWeb documents based on a deep learning classifier trained to identify structured and knowledge-rich samples. This classifier uses XLM-RoBERTa embeddings to score documents. To validate our approach, we pretrained 1B-parameter LLM models with a Llama-like architecture across multiple languages and… See the full description on the dataset page: https://huggingface.co/datasets/epfml/FineWeb-HQ.

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.

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.

Dataset Card for "commonsense_qa" Dataset Summary CommonsenseQA is a new multiple-choice question answering dataset that requires different types of commonsense knowledge to predict the correct answers . It contains 12,102 questions with one correct answer and four distractor answers. The dataset is provided in two major training/validation/testing set splits: "Random split" which is the main evaluation split, and "Question token split", see paper for details.… See the full description on the dataset page: https://huggingface.co/datasets/tau/commonsense_qa.

Dataset Card for HuggingFaceFW/finephrase Dataset Summary Synthetic data generated by DataTrove: Model: HuggingFaceTB/SmolLM2-1.7B-Instruct (main) Source dataset: HuggingFaceFW/fineweb-edu, config sample-350BT, split train Generation config: temperature=1.0, top_p=1.0, top_k=50, max_tokens=2048, model_max_context=8192 Speculative decoding: {"method":"suffix","num_speculative_tokens":32} System prompt: None Input column: text Prompt families: faq prompt Rewrite the… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/finephrase.

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.

Ettin Pre-training Data Phase 1 of 3: Diverse pre-training data mixture (1.7T tokens) used to train the Ettin model suite. This dataset contains the pre-training phase data used to train all Ettin encoder and decoder models. The data is provided in MDS format ready for use with Composer and the ModernBERT training repository. 📊 Data Composition Data Source Tokens (B) Percentage Description DCLM 837.2 49.1% High-quality web crawl data CC Head 356.6… See the full description on the dataset page: https://huggingface.co/datasets/jhu-clsp/ettin-pretraining-data.

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.

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

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.

Dataset Card for NatureBench NatureBench is a cross-discipline benchmark of 27 tasks distilled from peer-reviewed Nature-family publications, spanning 6 scientific domains. It is designed to evaluate whether AI coding agents can move beyond reproduction toward discovery: each task asks an agent to solve a real scientific machine-learning problem and is scored against the source paper's reported state of the art. 📄 arXiv paper: https://arxiv.org/abs/2606.24530 💻 GitHub code… See the full description on the dataset page: https://huggingface.co/datasets/JoeLiu996/NatureBench.

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

InternData-A1 InternData-A1 is a hybrid synthetic-real manipulation dataset containing over 630k trajectories and 7,433 hours across 4 embodiments, 18 skills, 70 tasks, and 227 scenes, covering rigid, articulated, deformable, and fluid-object manipulation. Your browser does not support the video tag. Your browser does not support the video tag.… See the full description on the dataset page: https://huggingface.co/datasets/InternRobotics/InternData-A1.