{
 "schema_version": 1,
 "generated": "2026-10-31",
 "id": "huggingface-lerobot--train-a-robot-policy-on-a-hub-dataset",
 "repo": "huggingface/lerobot",
 "repo_url": "https://github.com/huggingface/lerobot",
 "repo_slug": "huggingface-lerobot",
 "title": "Train a robot policy on a Hugging Face dataset",
 "page_title": "How to train a robot policy on a Hugging Face dataset with Lerobot",
 "summary": "Train an ACT policy on a public LeRobot dataset with one lerobot-train command, no robot needed.",
 "who": "A machine learning engineer curious about robot learning who does not own hardware yet.",
 "problem": "Robotics research code is often tied to one lab's robot and data format.",
 "outcome": "A trained ACT policy checkpoint from the lerobot/aloha_mobile_cabinet dataset.",
 "steps": [
  "Install with `pip install lerobot` and check the setup with lerobot-info",
  "Add training dependencies with the 'Lerobot[training]' extra",
  "Train with `lerobot-train` using `--policy.type=act`, `--dataset.repo_id=lerobot/aloha_mobile_cabinet` and `--policy.push_to_hub=false`",
  "Try other policies from the README table, such as Diffusion or SmolVLA, by changing policy.type",
  "Check the Compute Hardware Guide for GPU, RAM and training time per policy"
 ],
 "agent_prompt": "Using huggingface/lerobot, install the training extra and run lerobot-train with --policy.type=act on --dataset.repo_id=lerobot/aloha_mobile_cabinet with --policy.push_to_hub=false. Report training loss and where the checkpoint was saved.",
 "agents": [
  "claude-code",
  "codex",
  "cursor"
 ],
 "difficulty": "Intermediate",
 "time": "half a day",
 "basis": "readme",
 "caveat": "This card is written from the huggingface/lerobot README, not from a test run by Deduped. Before you start, make sure you have Python and pip. Check the repo for newer instructions before you rely on these steps.",
 "category": "Software and DevOps",
 "tags": [
  "Software and DevOps"
 ],
 "lang": "python",
 "requirements": [
  "Python and pip",
  "Extras for your task: lerobot[dataset], lerobot[training], or lerobot[core_scripts,feetech] for an SO-101 arm",
  "A GPU for training most policies (see the Compute Hardware Guide)",
  "Optional: a supported robot such as SO101, Koch or LeKiwi, and a Hugging Face account to push datasets and models"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": true,
 "score": 1.0,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/huggingface-lerobot/train-a-robot-policy-on-a-hub-dataset/",
 "md": "https://dedupedai.com/use-cases/huggingface-lerobot/train-a-robot-policy-on-a-hub-dataset/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/huggingface-lerobot--train-a-robot-policy-on-a-hub-dataset.json",
 "api_version": "v1"
}