Add model card

README.md

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+---
+library_name: lerobot
+tags:
+- molmoact2
+- robotics
+- lerobot
+- vla
+base_model: allenai/MolmoAct2
+---
+
+# molmoact2_block_stack_norm_fix
+
+Fine-tuned [MolmoAct2](https://huggingface.co/allenai/MolmoAct2) (action-expert-only) on SO101 data, with SO101 gripper normalization fix.
+
+| | |
+|---|---|
+| **Base model** | [allenai/MolmoAct2](https://huggingface.co/allenai/MolmoAct2) |
+| **Dataset** | [villekuosmanen/armnetbench_block_stack](https://huggingface.co/datasets/villekuosmanen/armnetbench_block_stack) |
+| **Task** | `block_stack` |
+| **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_block_stack](https://wandb.ai/pravsels/molmoact2_block_stack) |
+| **W&B run** | [eqx1ihxu](https://wandb.ai/pravsels/molmoact2_block_stack/runs/eqx1ihxu) |
+
+## Checkpoints
+
+| Step | Path |
+|------|------|
+| 002000 | `checkpoints/002000/pretrained_model/` |
+
+The latest step (`002000`) is also copied to the **repository root** for direct loading.
+
+## Usage
+
+```python
+from lerobot.policies.molmoact2.modeling_molmoact2 import MolmoAct2Policy
+policy = MolmoAct2Policy.from_pretrained("pravsels/molmoact2_block_stack_norm_fix")
+```