Datasets

GroundCUA: Grounding Computer Use Agents on Human Demonstrations 🌐 Website | 📑 Paper | 🤗 Dataset | 🤖 Models GroundCUA Dataset GroundCUA is a large and diverse dataset of real UI screenshots paired with structured annotations for building multimodal computer use agents. It covers 87 software platforms across productivity tools, browsers, creative tools, communication apps, development environments, and system utilities. GroundCUA is designed for research on GUI… See the full description on the dataset page: https://huggingface.co/datasets/ServiceNow/GroundCUA.

MegaPairs-Standard (Standardized Version) Dataset Summary This is a standardized, high-efficiency version of the JUNJIE99/MegaPairs dataset. Why use this version? The original dataset is distributed as a massive Tar archive containing millions of images, accompanied by a separate JSONL annotation file. The Problem: Using the original format requires extracting terabytes of small files (which can exhaust disk inodes) or writing complex logic to read from archives. It… See the full description on the dataset page: https://huggingface.co/datasets/86Cao/MegaPairs-Standard.

This dataset was created using LeRobot. DROID: A Large-Scale In-the-Wild Robot Manipulation Dataset One of the biggest open-source dataset for robotics with 27.044,326 frames, 92,223 episodes, 31,308 unique task description in natural language. Ported from Tensorflow Dataset format (2TB) to LeRobotDataset format (400GB) with the help from IPEC-COMMUNITY. Visualization: LeRobot Homepage: Droid Paper: Arxiv License: apache-2.0 Dataset Structure meta/info.json: {… See the full description on the dataset page: https://huggingface.co/datasets/cadene/droid.

GUI-360°: A Comprehensive Dataset And Benchmark For Computer-Using Agents Paper | Code GUI-360° is a large-scale, comprehensive dataset and benchmark suite designed to advance Computer-Using Agents (CUAs). 🎯 Key Features 🔢 1.2M+ executed action steps across thousands of trajectories 💼 Popular Windows office applications (Word, Excel, PowerPoint) 📸 Full-resolution screenshots with accessibility metadata 🎨 Multi-modal trajectories with reasoning traces ✅ Both… See the full description on the dataset page: https://huggingface.co/datasets/vyokky/GUI-360.

Multilingual Speech Commands Dataset (15 Languages, Augmented) This dataset contains augmented speech command samples in 15 languages, derived from multiple public datasets. Only commands that overlap with the Google Speech Commands (GSC) vocabulary are included, making the dataset suitable for multilingual keyword spotting tasks aligned with GSC-style classification. Audio samples have been augmented using standard audio techniques to improve model robustness (e.g., time-shifting… See the full description on the dataset page: https://huggingface.co/datasets/artur-muratov/multilingual-speech-commands-15lang.

arXiv Papers by Subject A reorganised version of the nick007x/arxiv-papers dataset, partitioned by subject code, year, and month for efficient selective access. Dataset Description This dataset contains metadata for over 2.5 million arXiv papers, organised into a hierarchical directory structure that allows users to download only the specific subjects and time periods they need, rather than the entire dataset. Motivation The original nick007x/arxiv-papers… See the full description on the dataset page: https://huggingface.co/datasets/permutans/arxiv-papers-by-subject.

🍃 MINT-1T:Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens 🍃 MINT-1T is an open-source Multimodal INTerleaved dataset with 1 trillion text tokens and 3.4 billion images, a 10x scale-up from existing open-source datasets. Additionally, we include previously untapped sources such as PDFs and ArXiv papers. 🍃 MINT-1T is designed to facilitate research in multimodal pretraining. 🍃 MINT-1T is created by a team from the University of Washington in… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/MINT-1T-PDF-CC-2023-50.

Dataset Card for YODAS-Granary Repository: NeMo-speech-data-processor: Granary Paper: Granary: Speech Recognition and Translation Dataset in 25 European Languages Shared by: ESPnet Dataset Description YODAS-Granary is a curated subset of the larger nvidia/Granary dataset, focusing on high-quality pseudo-labeled speech data for Automatic Speech Recognition (ASR) and Automatic Speech Translation (AST) across 23 European languages. Overview… See the full description on the dataset page: https://huggingface.co/datasets/espnet/yodas-granary.

Dataset containing synthetically generated (by GPT-3.5 and GPT-4) short stories that only use a small vocabulary. Described in the following paper: https://arxiv.org/abs/2305.07759. The models referred to in the paper were trained on TinyStories-train.txt (the file tinystories-valid.txt can be used for validation loss). These models can be found on Huggingface, at roneneldan/TinyStories-1M/3M/8M/28M/33M/1Layer-21M. Additional resources: tinystories_all_data.tar.gz - contains a superset of… See the full description on the dataset page: https://huggingface.co/datasets/roneneldan/TinyStories.

Vchitect-T2V-Dataverse Vchitect Team1  1Shanghai Artificial Intelligence Laboratory  Paper | Project Page | Data Overview The Vchitect-T2V-Dataverse is the core dataset used to train our text-to-video diffusion model, Vchitect-2.0: Parallel Transformer for Scaling Up Video Diffusion Models. It comprises 14 million high-quality videos collected from the Internet, each paired with detailed textual… See the full description on the dataset page: https://huggingface.co/datasets/Vchitect/Vchitect_T2V_DataVerse.

LLaVA-OneVision-1.5 Instruction Data Paper | Code 📌 Introduction This dataset, LLaVA-OneVision-1.5-Instruct, was collected and integrated during the development of LLaVA-OneVision-1.5. LLaVA-OneVision-1.5 is a novel family of Large Multimodal Models (LMMs) that achieve state-of-the-art performance with significantly reduced computational and financial costs. This meticulously curated 22M instruction dataset (LLaVA-OneVision-1.5-Instruct) is part of a comprehensive and… See the full description on the dataset page: https://huggingface.co/datasets/mvp-lab/LLaVA-OneVision-1.5-Instruct-Data.

This is the wikipedia split used to evaluate the Dense Passage Retrieval (DPR) model. It contains 21M passages from wikipedia along with their DPR embeddings. The wikipedia articles were split into multiple, disjoint text blocks of 100 words as passages.

Dataset Card for "ag_news" Dataset Summary AG is a collection of more than 1 million news articles. News articles have been gathered from more than 2000 news sources by ComeToMyHead in more than 1 year of activity. ComeToMyHead is an academic news search engine which has been running since July, 2004. The dataset is provided by the academic comunity for research purposes in data mining (clustering, classification, etc), information retrieval (ranking, search, etc), xml… See the full description on the dataset page: https://huggingface.co/datasets/fancyzhx/ag_news.

🚀 AutoMathText-V2: A 2.46 Trillion Token AI-Curated STEM Pretraining Dataset   🎉 AutoMathText-v2 has surpassed 1.5 million downloads! We'd love to know how you're using it. Please take 1 minute to fill out our use case survey. Your feedback will directly shape the future roadmap of this dataset.👉 Share your use case here 📊 AutoMathText-V2 consists of 2.46 trillion tokens of high-quality, deduplicated text spanning web content, mathematics, code, reasoning, and… See the full description on the dataset page: https://huggingface.co/datasets/OpenSQZ/AutoMathText-V2.

TL;DR of L2D, the world's largest self-driving dataset! Read more about L2D on the official Huggingface blog: LeRobot goes to driving school 90+ TeraBytes of multimodal data (5000+ hours of driving) from 30 cities in Germany 6x surrounding HD cameras and complete vehicle state: Speed/Heading/GPS/IMU Continuous: Gas/Brake/Steering and discrete actions: Gear/Turn Signals Environment state: Lane count, Road type (highway|residential), Road surface (asphalt, cobbled, sett), Max speed limit.… See the full description on the dataset page: https://huggingface.co/datasets/yaak-ai/L2D.

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.

Dataset Card for "ArtifactAI/arxiv_s2orc_parsed" Dataset Description https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_s2orc_parsed Dataset Summary AlgorithmicResearchGroup/arxiv_s2orc_parsed is a subset of the AllenAI S2ORC dataset, a general-purpose corpus for NLP and text mining research over scientific papers, The dataset is filtered strictly for ArXiv papers, including the full text for each paper. Github links have been extracted from each… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_s2orc_parsed.

ColliderML: Dataset Release 1 Dataset Description This dataset contains simulated high-energy physics collision events generated using the Open Data Detector (ODD) geometry within the Key4hep and ACTS (A Common Tracking Software) frameworks, representing a generic collider detector similar to those at the HL-LHC. Dataset Summary Collision Energy: 14 TeV (proton-proton) Detector: Open Data Detector (ODD) Simulation: DD4hep + Geant4 + ACTS Format: Apache Parquet… See the full description on the dataset page: https://huggingface.co/datasets/CERN/ColliderML-Release-1.