| # 🤗 LeRobot Notebooks | |
| This repository contains example notebooks for using LeRobot. These notebooks demonstrate how to train policies on real or simulation datasets using standardized policies. | |
| --- | |
| ### Training ACT | |
| [ACT](https://huggingface.co/papers/2304.13705) (Action Chunking Transformer) is a transformer-based policy architecture for imitation learning that processes robot states and camera inputs to generate smooth, chunked action sequences. | |
| We provide a ready-to-run Google Colab notebook to help you train ACT policies using datasets from the Hugging Face Hub, with optional logging to Weights & Biases. | |
| | Notebook | Colab | | |
| | :------------------------------------------------------------------------------------------------------ | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | |
| | [Train ACT with LeRobot](https://github.com/huggingface/notebooks/blob/main/lerobot/training-act.ipynb) | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/lerobot/training-act.ipynb) | | |
| Expected training time for 100k steps: ~1.5 hours on an NVIDIA A100 GPU with batch size of `64`. | |
| ### Training SmolVLA | |
| [SmolVLA](https://huggingface.co/papers/2506.01844) is a small but efficient Vision-Language-Action model. It is compact in size with 450 M-parameter and is developed by Hugging Face. | |
| We provide a ready-to-run Google Colab notebook to help you train SmolVLA policies using datasets from the Hugging Face Hub, with optional logging to Weights & Biases. | |
| | Notebook | Colab | | |
| | :-------------------------------------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | |
| | [Train SmolVLA with LeRobot](https://github.com/huggingface/notebooks/blob/main/lerobot/training-smolvla.ipynb) | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/lerobot/training-smolvla.ipynb) | | |
| Expected training time for 20k steps: ~5 hours on an NVIDIA A100 GPU with batch size of `64`. | |