| license: apache-2.0 | |
| library_name: lerobot | |
| pipeline_tag: robotics | |
| tags: | |
| - robotics | |
| - lerobot | |
| - act | |
| - so101 | |
| - simstudio | |
| datasets: | |
| - alexhegit/so101-simstudio-lab01-pnp | |
| # SO-101 Lab01 Pick-and-Place — ACT | |
| ACT policy fine-tuned on expert demonstrations collected and validated with **[SO-101 SimStudio](https://github.com/rocPAI-Forge/so101-simstudio)** (MuJoCo sim2sim, leader-arm teleop). | |
| **Training data:** [alexhegit/so101-simstudio-lab01-pnp](https://huggingface.co/datasets/alexhegit/so101-simstudio-lab01-pnp) | |
| ## Documentation | |
| | Resource | Link | | |
| |----------|------| | |
| | SimStudio repo | [rocPAI-Forge/so101-simstudio](https://github.com/rocPAI-Forge/so101-simstudio) | | |
| | Lab 01 walkthrough (record → train → eval) | [labs/lab01_pnp/lab01_pnp.md](https://github.com/rocPAI-Forge/so101-simstudio/blob/main/labs/lab01_pnp/lab01_pnp.md) | | |
| For dataset layout, training commands, eval configs, and reference metrics, see **Lab 01** in the repo above. | |
| ## Quick load | |
| ```python | |
| from lerobot.policies.act.modeling_act import ACTPolicy | |
| policy = ACTPolicy.from_pretrained("alexhegit/so101-simstudio-lab01-pnp-act") | |
| ``` | |
| Sim2sim eval in MuJoCo: follow **§6 Policy eval** in [lab01_pnp.md](https://github.com/rocPAI-Forge/so101-simstudio/blob/main/labs/lab01_pnp/lab01_pnp.md) (ACT configs under `labs/lab01_pnp/configs/rollout_act*.yaml`). | |