Instructions to use pravsels/molmoact2_eyedrops_shelf_norm_fix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use pravsels/molmoact2_eyedrops_shelf_norm_fix with LeRobot:
- Notebooks
- Google Colab
- Kaggle
molmoact2_eyedrops_shelf_norm_fix
Fine-tuned MolmoAct2 (action-expert-only) on SO101 data, with SO101 gripper normalization fix.
| Base model | allenai/MolmoAct2 |
| Dataset | pravsels/object_top_shelf_remote |
| Task | eyedrops_shelf |
| Action dim | 6 (single-arm) |
| Cameras | top, wrist, front |
| Normalization | MEAN_STD (action + state + gripper), IDENTITY (visual) |
| Training | Isambard GH200, batch 64, bf16, gradient checkpointing |
| W&B project | molmoact2_eyedrops_shelf |
| W&B run | g9j1z7qw |
Checkpoints
| Step | Path |
|---|---|
| 002000 | checkpoints/002000/pretrained_model/ |
The latest step (002000) is also copied to the repository root for direct loading.
Usage
from lerobot.policies.molmoact2.modeling_molmoact2 import MolmoAct2Policy
policy = MolmoAct2Policy.from_pretrained("pravsels/molmoact2_eyedrops_shelf_norm_fix")
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Model tree for pravsels/molmoact2_eyedrops_shelf_norm_fix
Base model
allenai/MolmoAct2