| | --- |
| | datasets: |
| | - shuohsuan/grasp0 |
| | - shuohsuan/grasp1 |
| | - shuohsuan/grasp2 |
| | - shuohsuan/grasp3 |
| | library_name: lerobot |
| | license: apache-2.0 |
| | model_name: act |
| | pipeline_tag: robotics |
| | tags: |
| | - act |
| | - lerobot |
| | - robotics |
| | --- |
| | |
| | # Model Card for act |
| |
|
| | <!-- Provide a quick summary of what the model is/does. --> |
| |
|
| |
|
| | [Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high success rates. |
| |
|
| |
|
| | This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot). |
| | See the full documentation at [LeRobot Docs](https://huggingface.co/docs/lerobot/index). |
| |
|
| | --- |
| |
|
| | ## How to Get Started with the Model |
| |
|
| | For a complete walkthrough, see the [training guide](https://huggingface.co/docs/lerobot/il_robots#train-a-policy). |
| | Below is the short version on how to train and run inference/eval: |
| |
|
| | ### Train from scratch |
| |
|
| | ```bash |
| | python -m lerobot.scripts.train \ |
| | --dataset.repo_id=${HF_USER}/<dataset> \ |
| | --policy.type=act \ |
| | --output_dir=outputs/train/<desired_policy_repo_id> \ |
| | --job_name=lerobot_training \ |
| | --policy.device=cuda \ |
| | --policy.repo_id=${HF_USER}/<desired_policy_repo_id> |
| | --wandb.enable=true |
| | ``` |
| |
|
| | *Writes checkpoints to `outputs/train/<desired_policy_repo_id>/checkpoints/`.* |
| |
|
| | ### Evaluate the policy/run inference |
| |
|
| | ```bash |
| | python -m lerobot.record \ |
| | --robot.type=so100_follower \ |
| | --dataset.repo_id=<hf_user>/eval_<dataset> \ |
| | --policy.path=<hf_user>/<desired_policy_repo_id> \ |
| | --episodes=10 |
| | ``` |
| |
|
| | Prefix the dataset repo with **eval\_** and supply `--policy.path` pointing to a local or hub checkpoint. |
| | |
| | --- |
| | |
| | ## Model Details |
| | |
| | * **License:** apache-2.0 |
