Add model card with W&B link

README.md

@@ -0,0 +1,39 @@
+---
+library_name: gr00t
+tags:
+- gr00t
+- gr00t-n1.7
+- robotics
+- vla
+base_model: nvidia/GR00T-N1.7-3B
+---
+
+# groot1.7_fold_tea_towel
+
+Fine-tuned [GR00T N1.7-3B](https://huggingface.co/nvidia/GR00T-N1.7-3B) on SO101 data (`fold_tea_towel`).
+
+| | |
+|---|---|
+| **Base model** | [nvidia/GR00T-N1.7-3B](https://huggingface.co/nvidia/GR00T-N1.7-3B) |
+| **Dataset** | [villekuosmanen/armnetbench_fold_tea_towel](https://huggingface.co/datasets/villekuosmanen/armnetbench_fold_tea_towel) |
+| **Task** | `fold_tea_towel` |
+| **Training** | Isambard-AI GH200, batch 64, action horizon 16 |
+| **W&B project** | [groot1.7_fold_tea_towel](https://wandb.ai/pravsels/groot1.7_fold_tea_towel) |
+| **W&B run** | [qp91sjl0](https://wandb.ai/pravsels/groot1.7_fold_tea_towel/runs/qp91sjl0) |
+
+## Checkpoints
+
+| Step | Loss | Path |
+|------|------|------|
+| 6,000 | 0.0262 | `checkpoints/6000/pretrained_model/` |
+| 4,000 | 0.0432 | `checkpoints/4000/pretrained_model/` |
+
+## Usage
+
+Load from a specific step:
+
+```python
+from pathlib import Path
+# Use checkpoints/<step>/pretrained_model/ with the GR00T inference stack
+ckpt = "pravsels/groot1.7_fold_tea_towel/checkpoints/6000/pretrained_model"
+```