| datasets: y1y2y3/so101_test4 | |
| 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 | |
| lerobot-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 | |
| 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 |