Instructions to use pravsels/molmoact2_transfer_cube_norm_fix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use pravsels/molmoact2_transfer_cube_norm_fix with LeRobot:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
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Download README.md from pravsels/molmoact2_transfer_cube_norm_fix: direct link, hf CLI and curl.
- Browser
- Download file 1.37 kB
-
https://huggingface.co/pravsels/molmoact2_transfer_cube_norm_fix/resolve/main/README.md
- Command line
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hf download hf://pravsels/molmoact2_transfer_cube_norm_fix/README.md
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curl -L -o README.md https://huggingface.co/pravsels/molmoact2_transfer_cube_norm_fix/resolve/main/README.md
1.37 kB
metadata
library_name: lerobot
tags:
- molmoact2
- robotics
- lerobot
- vla
- bimanual
base_model: allenai/MolmoAct2
molmoact2_transfer_cube_norm_fix
Fine-tuned MolmoAct2 (action-expert-only) on SO101 data, with SO101 gripper normalization fix.
| Base model | allenai/MolmoAct2 |
| Dataset | villekuosmanen/armnetbench_transfer_cube |
| Task | transfer_cube |
| Action dim | 12 (bimanual) |
| Cameras | top, left_wrist, right_wrist |
| Normalization | MEAN_STD (action + state + gripper), IDENTITY (visual) |
| Training | Isambard GH200, batch 64, bf16, gradient checkpointing |
| W&B project | molmoact2_transfer_cube |
| W&B run | kfileqwv |
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_transfer_cube_norm_fix")