physical-ai-datasets

name	physical-ai-datasets
description	Use when the user wants to find, download, or pick a NVIDIA Physical AI dataset on Hugging Face for autonomous-vehicle, robotics, spatial intelligence, manipulation, or neural-reconstruction workflows. Catalog of every dataset under huggingface.co/nvidia with the `PhysicalAI-` prefix, organised by domain (AV, Robotics-Manipulation, Robotics-GR00T, Robotics-mindmap, Robotics-NuRec, Spatial Intelligence, Grasping, Healthcare, Sim-Ready, Material properties), with per-dataset size, format, gating, license, and the downstream sibling skill (`ncore`, `nre`, `asset-harvester`, `nurec-fixer`) or upstream tool (Isaac Sim, CARLA, Isaac-GR00T, Cosmos-*) that consumes it. Do NOT use as a runtime — it routes you elsewhere. Trigger keywords: nvidia physical ai dataset, PhysicalAI- dataset, hf nvidia dataset, NCore dataset, NuRec dataset, GR00T dataset, GraspGen, SimReady, Cosmos-Drive-Dreams, Lyra SDG, Open-H-Embodiment, huggingface-cli download, physical_ai_av, dataset gated, RDS-HQ.
version	0.1.0
tools	["Shell","Read","Write"]
license	CC-BY-4.0 AND Apache-2.0
dependencies	["bash","python","huggingface_hub"]
compatibility	All listed datasets are hosted on Hugging Face and require `huggingface_hub` (CLI: `huggingface-cli` / new `hf` shim) plus a HF user access token. Several datasets are GATED — they need explicit license acceptance on the HF dataset page before any token can pull them. Storage ranges from <1 GB to >100 TB (PhysicalAI-Autonomous-Vehicles, 133 TB).
metadata	{"author":"NVIDIA Physical AI","tags":["dataset-catalog","physical-ai","huggingface","autonomous-vehicles","robotics"],"hf_org":"https://huggingface.co/nvidia","hf_collection":"https://huggingface.co/collections/nvidia/physical-ai","cosmos_dataset_search":"https://build.nvidia.com/nvidia/cosmos-dataset-search","pai_av_toolkit":"https://github.com/NVlabs/physical_ai_av"}

NVIDIA Physical AI Datasets (Hugging Face)

Purpose

Help the agent find, evaluate, and download an NVIDIA PhysicalAI-* dataset on Hugging Face that fits the user's downstream task — autonomous-vehicle reconstruction, robotics manipulation, GR00T post-training, spatial-intelligence research, grasping, or sim-ready content — and then hand off to the sibling skill (ncore, nre, asset-harvester, nurec-fixer) or upstream NVIDIA tool that actually consumes it.

Use this skill when: the user asks "is there an NVIDIA dataset for X?", "where do I get NCore / NuRec / GR00T sample data?", or is shopping the Hugging Face NVIDIA org for PhysicalAI-* collections.

Do NOT use this skill when:

• The user already knows the dataset and just wants to run a pipeline — jump straight to the consuming skill.
• The user needs a non-NVIDIA dataset (Waymo, nuScenes, KITTI, …) — this catalog is NVIDIA-only.
• The user wants to train Cosmos / GR00T / Isaac Sim itself — that's the upstream tool's job, not this catalog's.

Overview

Catalog of NVIDIA's open Physical AI dataset family on Hugging Face. Pick by task (Section 2 § lookup table) or family (Sections 3–10). Every entry lists: dataset path, size, format, license, gating, and the downstream skill in this repo that consumes it.

Source of truth: https://huggingface.co/nvidia (filter PhysicalAI-) and the curated Physical AI collection. When upstream cards drift, re-check the HF page; this skill mirrors the cards as of Apr 2026.

Prerequisites

• HuggingFace account with the dataset card opened in a browser at least once, and the gating checkbox accepted on every dataset you intend to download.
• HuggingFace user access token exported as HF_TOKEN (create at https://huggingface.co/settings/tokens).
• git, git-lfs, and huggingface_hub[cli] on PATH.
• Storage room sized to the dataset you're pulling (see the per-row size column; some are < 1 GB, the AV dataset is 133 TB — always pre-filter with --include or physical_ai_av).

Verifying secrets safely

Always check token presence with or a length-only shell test; never write ad-hoc bash that interpolates values. The common one-liner