Model Hub

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.

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 CML-TTS Dataset Summary CML-TTS is a recursive acronym for CML-Multi-Lingual-TTS, a Text-to-Speech (TTS) dataset developed at the Center of Excellence in Artificial Intelligence (CEIA) of the Federal University of Goias (UFG). CML-TTS is a dataset comprising audiobooks sourced from the public domain books of Project Gutenberg, read by volunteers from the LibriVox project. The dataset includes recordings in Dutch, German, French, Italian, Polish… See the full description on the dataset page: https://huggingface.co/datasets/ylacombe/cml-tts.

🚀 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.

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.

GPT-Image-Edit-1.5M A Million-Scale, GPT-Generated Image Dataset 📃Arxiv | 🌐 Project Page | 💻Github GPT-Image-Edit-1.5M is a comprehensive image editing dataset that is built upon HQ-Edit, UltraEdit, OmniEdit and Complex-Edit, with all output images regenerated with GPT-Image-1. 📣 News [2025.08.20] 🚀 We provide a script for multi-process downloading. See Multi-process Download. [2025.07.27] 🤗 We release GPT-Image-Edit, a state-of-the-art image editing model with… See the full description on the dataset page: https://huggingface.co/datasets/UCSC-VLAA/GPT-Image-Edit-1.5M.