| | --- |
| | pipeline_tag: robotics |
| | tags: |
| | - lerobot |
| | library_name: lerobot |
| | datasets: |
| | - TekbotRobotics/svla_so101_pickplace_flags_sorting |
| | --- |
| | ## SmolVLA: A vision-language-action model for affordable and efficient robotics |
| |
|
| | Resources and technical documentation: |
| |
|
| |
|
| | [Train using Google Colab Notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/lerobot/training-smolvla.ipynb#scrollTo=ZO52lcQtxseE) |
| |
|
| | [SmolVLA HF Documentation](https://huggingface.co/docs/lerobot/smolvla) |
| |
|
| | Designed by Tekbot Robotics and Inspired from Hugging Face. |
| |
|
| | This model was finetuned on [hugging Face base model](https://huggingface.co/lerobot/smolvla_base/). |
| |
|
| | Before proceeding to the next steps, you need to properly install the environment by following [Installation Guide](https://huggingface.co/docs/lerobot/installation) on the docs. |
| |
|
| | Install smolvla extra dependencies: |
| | ```bash |
| | pip install -e ".[smolvla]" |
| | ``` |
| |
|
| | Example of finetuning the smolvla pretrained model (`smolvla_base`): |
| | ```bash |
| | python lerobot/scripts/train.py \ |
| | --policy.path=lerobot/smolvla_base \ |
| | --dataset.repo_id=TekbotRobotics/svla_so101_pickplace_flags_sorting \ |
| | --batch_size=8 \ |
| | --steps=2000 \ |
| | --output_dir=outputs/train/my_smolvla \ |
| | --job_name=my_smolvla_training \ |
| | --policy.device=cuda \ |
| | --wandb.enable=true |
| | ``` |
| |
|
