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LeRobot - AI Robotics Tool

Overview

LeRobot is an open-source robotics research toolkit hosted on GitHub that bundles models, datasets, and utilities to accelerate end-to-end learning for real-world robotics. According to the GitHub repository, the project focuses on PyTorch-first implementations, providing reusable training pipelines, model checkpoints, and dataset loaders tailored to robot perception, control, and learning workflows. The codebase is organized to let researchers and engineers move from simulation to real robot experiments by combining data handling, model architectures, and evaluation scripts. LeRobot is positioned as a practical resource rather than a single-model library: it collects baseline models and prebuilt training recipes, dataset conversion and loading tools, and examples showing how to run training and evaluation on physical hardware or simulators. The repository emphasizes reproducibility and end-to-end examples so teams can reproduce published baselines, iterate on models, and plug in custom hardware interfaces or sensors. For detailed installation instructions, model descriptions, and up-to-date release notes, consult the project README and the repository’s issue/PR history on GitHub.

Installation

Install via pip:

git clone https://github.com/huggingface/lerobot.git
cd lerobot
pip install -e .

Key Features

  • PyTorch-native training pipelines and example scripts for robotics learning.
  • Dataset loaders and conversion utilities for common robotics data formats.
  • Reference model architectures and saved checkpoints for baseline comparisons.
  • End-to-end evaluation scripts for simulation-to-real and on-hardware tests.
  • Tools for logging, reproducibility, and integration with common experiment setups.

Community

LeRobot is developed openly on GitHub, with the repository serving as the canonical source for code, issues, and pull requests. Community engagement primarily occurs through GitHub issues and pull requests where users report bugs, request features, and contribute improvements. The project links to example notebooks and reproducibility artifacts to help new users reproduce baselines. For real-time discussion or broader community adoption, contributors and users also reference Hugging Face forums and associated documentation; check the repository’s issue tracker and PR history for recent activity and contributor statistics.

Last Refreshed: 2026-01-09

Key Information

  • Category: Robotics
  • Type: AI Robotics Tool
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