Add model card

README.md

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+---
+license: apache-2.0
+tags:
+  - robotics
+  - pi0
+  - bin-packing
+  - openpi
+---
+
+# pi0.5 Bin Pack — Single Dataset Baseline
+
+Fine-tuned [pi0.5](https://github.com/Physical-Intelligence/openpi) checkpoint for coffee capsule bin packing, trained on a single dataset of ~200 teleoperated episodes. This serves as the base checkpoint for the reward recap experiments.
+
+## Config
+
+- **Config name:** `pi05_bin_pack_coffee_capsules_delta_single_dataset`
+- **Model:** pi0.5 (`pi05=True`, `action_horizon=50`)
+- **Batch size:** 36
+- **Learning rate:** 5e-5 cosine decay (10k warmup)
+- **Optimizer:** AdamW (gradient clip norm 1.0)
+- **EMA decay:** 0.999
+- **Delta actions:** enabled
+- **Weight init:** `weights/pi05_base/params` (pi0.5 base weights)
+- **Training steps:** 30,000
+
+## Dataset
+
+- `villekuosmanen/bin_pick_pack_coffee_capsules` (~200 teleoperated episodes)
+
+## Checkpoint Hash
+
+Verify integrity with `tar cf - -C checkpoints/29999 params | sha256sum`.
+
+| Step | SHA-256 |
+|------|---------|
+| 29,999 | `bb051b5a3ee10adae7ee5313102fd7157e49d77a12a3b9a48e0688617108f9b0` |
+
+## Downstream
+
+This checkpoint is the weight init for the reward recap experiments:
+
+- [pi05-bin-pack-reward-recap-positive-only](https://huggingface.co/pravsels/pi05-bin-pack-reward-recap-positive-only)
+- [pi05-bin-pack-reward-recap-mixed](https://huggingface.co/pravsels/pi05-bin-pack-reward-recap-mixed)
+
+## Repo Structure
+
+```
+assets/                      # Norm stats + valid indices for inference
+checkpoints/29999/params/    # Model weights (params only)
+README.md                    # This file
+```
+
+## Usage
+
+```python
+from openpi.training.config import get_config
+from openpi.serving.policy_server import PolicyServer
+
+config = get_config("pi05_bin_pack_coffee_capsules_delta_single_dataset")
+server = PolicyServer(config, checkpoint_path="checkpoints/29999/params")
+```