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How to train a robot policy on a Hugging Face dataset with Lerobot

Train an ACT policy on a public LeRobot dataset with one lerobot-train command, no robot needed.

Short answer: Install with pip install lerobot and check the setup with lerobot-info; then 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. All steps.

Who it is forA machine learning engineer curious about robot learning who does not own hardware yet.

The problemRobotics research code is often tied to one lab's robot and data format.

The outcomeA trained ACT policy checkpoint from the lerobot/aloha_mobile_cabinet dataset.

What you need first

  • 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

Steps

  1. Install with pip install lerobot and check the setup with lerobot-info
  2. Add training dependencies with the 'Lerobot[training]' extra
  3. Train with lerobot-train using --policy.type=act, --dataset.repo_id=lerobot/aloha_mobile_cabinet and --policy.push_to_hub=false
  4. Try other policies from the README table, such as Diffusion or SmolVLA, by changing policy.type
  5. Check the Compute Hardware Guide for GPU, RAM and training time per policy

Prompt for your agent

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.

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.

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Using the Deduped MCP, get the setup steps for huggingface/lerobot and "Train a robot policy on a Hugging Face dataset"

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