Lerobot

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LeRobot is an AI Agents & Automation tool that makes AI for robotics more accessible with end-to-end learning. It provides models, datasets, and tools for real-world robotics in PyTorch.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is lerobot?

LeRobot, developed by Hugging Face, aims to democratize AI for robotics by offering a comprehensive open-source framework for end-to-end learning. It features a hardware-agnostic, Python-native interface for standardized control across diverse robotic platforms, from low-cost arms to humanoids. The tool introduces a standardized, scalable LeRobotDataset format (Parquet + MP4/images) hosted on the Hugging Face Hub, facilitating efficient storage, streaming, and visualization of large robotic datasets. LeRobot also implements state-of-the-art policies in pure PyTorch for Imitation Learning, Reinforcement Learning, and Vision-Language-Action models, with tools for instrumenting and inspecting the training process. It supports evaluation in simulation or on real hardware using a unified script, including standard benchmarks like LIBERO and MetaWorld.

Best used for

Ideal for developers and data scientists who need to build, train, and deploy AI models for real-world robotics, manage large robotic datasets, and evaluate policy performance. Especially valuable for those seeking an open-source, PyTorch-based framework with hardware-agnostic control.

Common actions

develop robot AI

train robot models

manage robotic datasets

evaluate robot policies

collaborationopen-sourceworkflowsface swappinggithub copilot"AI Agents"low-code/no-codedeepfakeautomated workflow

Capabilities

Key features

Hardware-agnostic robot control
Standardized LeRobotDataset format
State-of-the-art policies
Unified evaluation script
Hugging Face Hub integration
PyTorch implementation

Target Audience

developerdata scientist

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What types of robots does LeRobot support?

LeRobot provides a unified Robot class interface that supports a wide range of robots and teleoperation devices, including SO100, LeKiwi, Koch, HopeJR, OMX, EarthRover, Reachy2, Gamepads, Keyboards, Phones, OpenARM, and Unitree G1. It is also designed to be extensible for custom robots.

How does LeRobot handle robotic datasets?

LeRobot uses the LeRobotDataset format, which consists of synchronized MP4 videos (or images) for vision and Parquet files for state/action data. These datasets are integrated with the Hugging Face Hub, allowing for efficient storage, streaming, and visualization, with tools for managing episodes and features.

What kind of AI models can be implemented with LeRobot?

LeRobot implements state-of-the-art policies in pure PyTorch, covering Imitation Learning (ACT, Diffusion, VQ-BeT, Multitask DiT Policy), Reinforcement Learning (HIL-SERL, TDMPC & QC-FQL), and Vision-Language-Action (Pi0Fast, Pi0.5, GR00T N1.5, SmolVLA, XVLA) models. Users can also implement their own custom policies.

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