| library_name: lerobot | |
| license: apache-2.0 | |
| pipeline_tag: robotics | |
| tags: | |
| - robotics | |
| # Model Card for act_so101_test | |
| <!-- Provide a quick summary of what the model is/does. --> | |
| 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 lerobot/scripts/train.py \ | |
| --dataset.repo_id=<user_or_org>/<dataset> \ | |
| --policy.type=act \ | |
| --output_dir=outputs/train/<desired_policy_repo_id> \ | |
| --job_name=lerobot_training \ | |
| --policy.device=cuda \ | |
| --policy.repo_id=<user_or_org>/<desired_policy_repo_id> \ | |
| --wandb.enable=true | |
| ``` | |
| *Writes checkpoints to `outputs/train/<desired_policy_repo_id>/checkpoints/`.* | |
| ### Evaluate the policy | |
| ```bash | |
| python -m lerobot.record \ | |
| --robot.type=so100_follower \ | |
| --dataset.repo_id=<user_or_org>/eval_<dataset> \ | |
| --policy.path=<user_or_org>/<desired_policy_repo_id> \ | |
| --episodes=10 | |
| ``` | |
| Prefix the dataset repo with **eval_** and supply `--policy.path` pointing to a local or hub checkpoint. | |
| --- |