datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
PhysicalAI-WorldModel-Synthetic-Autonomous-Driving-Scenarios
Dataset Description:
PhysicalAI-WorldModel-Synthetic-Autonomous-Driving-Scenarios is a large-scale synthetic video dataset of autonomous-driving scenes generated with NVIDIA's internal Omniverse simulation platform. Each clip is a temporally consistent multi-camera surround capture of one ego vehicle and surrounding traffic participants, paired with per-camera VLM captions. The dataset is designed to fill gaps in real-world driving data along two axes: (1) targeted long-tail… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/PhysicalAI-WorldModel-Synthetic-Autonomous-Driving-Scenarios.synth_datasetsynthesized_datasetPhysicalAI-WorldModel-Synthetic-Physical-Interaction-Scenes
PhysicalAI-WorldModel-Synthetic-Physical-Interaction-Scenes Dataset Card
Dataset Description
PhysicalAI-WorldModel-Synthetic-Physical-Interaction-Scenes is a large-scale synthetic dataset of physically-simulated multi-object interaction scenes, generated using NVIDIA Isaac Sim and the PhysX physics engine. It is designed to train and evaluate AI models on physical reasoning, rigid body dynamics, optical flow, depth estimation, and scene understanding.
Each clip… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/PhysicalAI-WorldModel-Synthetic-Physical-Interaction-Scenes.PhysicalAI-WorldModel-Synthetic-Warehouse-Operations-Scenes
PhysicalAI SDG-Warehouse
PhysicalAI SDG-Warehouse is a synthetic, fully-annotated video dataset of staged industrial-safety events captured in a simulated warehouse environment. It contains approximately 123k video clips, totaling roughly 412 hours of footage at 1920x1080 resolution and 30 frames per second, organized across four scenarios: a forklift near-miss with a human worker, a warehouse fire with worker evacuation, a forklift collision with a storage shelf, and a routine… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/PhysicalAI-WorldModel-Synthetic-Warehouse-Operations-Scenes.PhysicalAI-WorldModel-Synthetic-Digital-Human-Scenes
Dataset Description:
The SDG-SynHuman is a large-scale synthetic video dataset of digital humans rendered in diverse indoor and outdoor 3D environments. The dataset contains 236,937 clips, totaling approximately 5,841 hours of video, and is designed to support training and post-training of NVIDIA Cosmos world foundation models and related physical AI research.
Each sample is a temporally coherent 60-120 second video clip rendered at 1080p and 30 fps. Clips contain… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/PhysicalAI-WorldModel-Synthetic-Digital-Human-Scenes.synthehicle
Dataset Card for Synthehicle
Synthehicle is a massive CARLA-based synthehic multi-vehicle multi-camera tracking dataset and includes ground truth for 2D detection and tracking, 3D detection and tracking, depth estimation, and semantic, instance and panoptic segmentation.
All details can be found in our paper and git repository.
InFlux-Synth
InFlux++ Synth
InFlux++ Synth is a large-scale synthetic training dataset for the InFlux project, providing per-frame ground truth camera intrinsics and camera pose for videos with dynamic intrinsics.
The dataset contains 441,840 annotated frames from 1,841 procedurally generated high-resolution videos. Every video contains 240 frames at a resolution of 1280 × 720. The dataset spans indoor and nature scenes and features changing zoom and focus, dynamic objects, and realistic… See the full description on the dataset page: https://huggingface.co/datasets/princeton-vl/InFlux-Synth.Total_Editing_Synthetic_Video_Albedo_Fullqa_squadshifts_synthetic_randomTBA
OCR-Synthetic-Multilingual-v1
OCR-Synthetic-Multilingual-v1
Overview
Large-scale synthetically generated OCR training dataset for multilingual text detection and recognition. The data was produced using a heavily modified and extended version of SynthDoG (Synthetic Document Generator), originally introduced in the Donut project by Kim et al.
This dataset was used to train Nemotron OCR v2, a state-of-the-art multilingual OCR model that is part of the NVIDIA NeMo Retriever collection.
Languages… See the full description on the dataset page: https://huggingface.co/datasets/Arturito1/OCR-Synthetic-Multilingual-v1.OCR-Synthetic-Multilingual-v1
OCR-Synthetic-Multilingual-v1
Overview
Large-scale synthetically generated OCR training dataset for multilingual text detection and recognition. The data was produced using a heavily modified and extended version of SynthDoG (Synthetic Document Generator), originally introduced in the Donut project by Kim et al.
This dataset was used to train Nemotron OCR v2, a state-of-the-art multilingual OCR model that is part of the NVIDIA NeMo Retriever collection.
Languages… See the full description on the dataset page: https://huggingface.co/datasets/Nishant2414/OCR-Synthetic-Multilingual-v1.OCR-Synthetic-Multilingual-v1
OCR-Synthetic-Multilingual-v1
Dataset Description
Large-scale synthetically generated OCR training dataset for multilingual text detection and recognition. The data was produced using a heavily modified and extended version of SynthDoG (Synthetic Document Generator), originally introduced in the Donut project by Kim et al.
This dataset was used to train Nemotron OCR v2, a state-of-the-art multilingual OCR model that is part of the NVIDIA NeMo Retriever collection.… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/OCR-Synthetic-Multilingual-v1.SYNTH
SYNTH
Blog announcement
SYNTH is the first open generalist synthetic dataset for training small reasoning model end-to-end, jointly released by Pleias and the AI Alliance.
SYNTH includes 79,648,272 individual text samples, comprising over 41 billion words (about 75 billion tokens with Pleias tokenizer). It is based on the amplification of 58,698 articles from Wikipedia and made possible thanks to the Structured Wikipedia dataset from Wikimedia Enterprise.
SYNTH differs… See the full description on the dataset page: https://huggingface.co/datasets/PleIAs/SYNTH.OCR-Synthetic-Multilingual-v1
OCR-Synthetic-Multilingual-v1
Dataset Description
Large-scale synthetically generated OCR training dataset for multilingual text detection and recognition. The data was produced using a heavily modified and extended version of SynthDoG (Synthetic Document Generator), originally introduced in the Donut project by Kim et al.
This dataset was used to train Nemotron OCR v2, a state-of-the-art multilingual OCR model that is part of the NVIDIA NeMo Retriever collection.
This… See the full description on the dataset page: https://huggingface.co/datasets/YuanHo/OCR-Synthetic-Multilingual-v1.agent-task-recursive-task-synthesis
Apptainer pool for hamishivi/agent-task-recursive-task-synthesis
This repository hosts tmax-compatible SIF images and a unified download manifest. Training data and task archives are in hamishivi/agent-task-recursive-task-synthesis. The manifest includes earlier images hosted under hamishivi and new images hosted under TMaxxx; the downloader selects the correct repository and immutable commit for each image.
Apptainer images
The pool currently contains 29,501 / 29… See the full description on the dataset page: https://huggingface.co/datasets/TMaxxx/agent-task-recursive-task-synthesis.olmOCR-synthmix-1025
olmOCR-synthmix-1025
olmOCR-synthmix-1025 is a dataset of 2,186 single PDF pages, that have been synthetically rerendered into HTML by
claude-sonnet-4-20250514.
In total, across these PDF pages, 30,381 synthetic benchmark cases have been created, following the format of olmOCR-bench.
These documents contain no overlap with the original olmOCR-bench documents, and thus can be used as RLVR training
data to improve the performance of OCR engines.
Directory Structure… See the full description on the dataset page: https://huggingface.co/datasets/allenai/olmOCR-synthmix-1025.SynthVerseViewer is explicitly configured to read the parquet split only.
Citation
If you find this dataset useful, please cite:
@article{zhao2026SythnVerse,
title={SynthVerse: A Large-Scale Diverse Synthetic Dataset for Point Tracking},
author={Weiguang Zhao and Haoran Xu and Xingyu Miao and Qin Zhao and Rui Zhang and Kaizhu Huang and Ning Gao and Peizhou Cao and Mingze Sun and Mulin Yu and Tao Lu and Linning Xu and Junting Dong and Jiangmiao Pang},
journal={arXiv preprint… See the full description on the dataset page: https://huggingface.co/datasets/InternRobotics/SynthVerse.SynthCLIPSynthCI-30M
This repo contains SynthCI-30M which is the dataset proposed in "SynthCLIP: Are We Ready For a Fully Synthetic CLIP Training?". The dataset contains 30M synthetic text-image pairs covering a wide range of concepts.
"We will reach a time where machines will create machines."
Abstract
We present SynthCLIP, a novel framework for training CLIP models with entirely synthetic text-image pairs, significantly departing from previous methods relying on real… See the full description on the dataset page: https://huggingface.co/datasets/hammh0a/SynthCLIP.OCR-Synthetic-Multilingual-v1
OCR-Synthetic-Multilingual-v1
Dataset Description
Large-scale synthetically generated OCR training dataset for multilingual text detection and recognition. The data was produced using a heavily modified and extended version of SynthDoG (Synthetic Document Generator), originally introduced in the Donut project by Kim et al.
This dataset was used to train Nemotron OCR v2, a state-of-the-art multilingual OCR model that is part of the NVIDIA NeMo Retriever collection.… See the full description on the dataset page: https://huggingface.co/datasets/Felix92/OCR-Synthetic-Multilingual-v1.zendo-synthetic-data
Zendo Synthetic Visual Reasoning Dataset
Synthetic Zendo-style scenes with associated rules and per-scene tensor
representations. Each scene either follows ("positive", label=1) or violates
("negative", label=0) a rule that is given in natural language and as a Prolog
query.
Splits
split
scenes
train
56475
test
3344
rules total
3439
Layout
images/<split>/<batch>/<rule_id>/<scene_id>.png — rendered scene… See the full description on the dataset page: https://huggingface.co/datasets/sophia1ch/zendo-synthetic-data.nerf-synthetic-mirrorPhysicalAI-WorldModel-Synthetic-Embodied-Robot-Scenes
PhysicalAI WorldModel Synthetic Embodied Robot Scenes Dataset Card
Dataset Description
PhysicalAI WorldModel Synthetic Embodied Robot Scenes is a large-scale synthetic robotics video corpus generated from USD-based robotic simulation and rendering pipelines built around NVIDIA Isaac Sim, Omniverse, Isaac Lab, and related robot data-generation systems. It is designed to improve physical plausibility, embodiment persistence, task-conditioned robot behavior reasoning… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/PhysicalAI-WorldModel-Synthetic-Embodied-Robot-Scenes.synthetic_data_v5_finegrain_layout_relight_with_our_synthetic_data_coco_l_full_500kbanana-vidorev3-synthetic-arms
Banana ViDoRe v3 Synthetic Arms
Domain-separated ViDoRe v3 synthetic training arms for finance and industrial adaptation.
The Hub dataset uses finance and industrial as dataset configs/subsets. Within each config, splits separate
vlm_in_batch, vlm_ocr_bm25, banana_fullpipe, and hybrid_vlm_ocr_bm25_banana_fullpipe.
Generated at: 2026-06-29T11:49:45.670912+00:00
Total JSONL rows across configs/splits: 151691.
Images are stored once per subset under… See the full description on the dataset page: https://huggingface.co/datasets/vkehfdl1/banana-vidorev3-synthetic-arms.MVS-synthsynthetic-math-toolcall-deception
Synthetic Math Tool-Call Deception
200 paired multi-turn math-assistant trajectories (400 rows) for evaluating deception
detectors on mid-trajectory tool-call misreporting.
Each trajectory: a system prompt instructs the model to compute via an execute_python
tool under a stated tool-call limit, and requires every call to carry a running
call_index argument (1 for the first call, 2 for the second, …). The platform enforcing
the limit is said to only see the reported call_index… See the full description on the dataset page: https://huggingface.co/datasets/annahbanannah/synthetic-math-toolcall-deception.Big-Math-RL-Verified
Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models
Big-Math is the largest open-source dataset of high-quality mathematical problems, curated specifically for reinforcement learning (RL) training in language models. With over 250,000 rigorously filtered and verified problems, Big-Math bridges the gap between quality and quantity, establishing a robust foundation for advancing reasoning in LLMs.
Request Early Access to Private… See the full description on the dataset page: https://huggingface.co/datasets/SynthLabsAI/Big-Math-RL-Verified.transformers-synthetic-assets
transformers-synthetic-assets
Synthetic media fixtures for Transformers tests. These assets are generated from prompts or deterministic code and are not derived from third-party source files.
Synthetic-UAV-Flight-Trajectories
UAV Trajectory Dataset
Summary
This dataset comprises over 5000 random UAV (Unmanned Aerial Vehicle) trajectories collected over 20 hours of flight time. It is intended for training AI models such as trajectory prediction applications. The dataset is generated through an automated pipeline for the creation and preprocessing of UAV synthetic trajectories, making it ready for direct AI model training.
Data Description
The dataset features parameterized… See the full description on the dataset page: https://huggingface.co/datasets/riotu-lab/Synthetic-UAV-Flight-Trajectories.