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README.md

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+---
+license: apache-2.0
+library_name: lerobot
+pipeline_tag: robotics
+tags:
+  - lerobot
+  - robotics
+  - pi05
+  - so101
+  - imitation-learning
+datasets:
+  - CoRL2026-CSI/SO101-teleop_sort_blocks_100epi
+base_model: lerobot/pi05_base
+---
+
+# π0.5 — SO-101 `sort_blocks`
+
+Fine-tuned [`lerobot/pi05_base`](https://huggingface.co/lerobot/pi05_base) on 100 teleop episodes of the SO-101 `sort_blocks` task.
+
+## Model
+
+- **Architecture**: π0.5 (PaliGemma-2B VLM + Gemma-300M action expert, flow matching, 10 inference steps)
+- **Cameras**: `base_0_rgb`, `left_wrist_0_rgb`, `right_wrist_0_rgb` (224×224)
+- **State / Action dim**: 32 (padded) / 6 (SO-101)
+- **Action chunk**: 50
+- **dtype**: bfloat16
+
+Camera key rename (dataset → policy):
+```
+observation.images.top   → observation.images.base_0_rgb
+observation.images.wrist → observation.images.left_wrist_0_rgb
+```
+`right_wrist_0_rgb` is an empty camera slot for this single-arm setup.
+
+Action features (SO-101): `shoulder_pan, shoulder_lift, elbow_flex, wrist_flex, wrist_roll, gripper` (`.pos`).
+Normalization: `ACTION/STATE = MEAN_STD`, `VISUAL = IDENTITY`.
+
+## Data
+
+[`CoRL2026-CSI/SO101-teleop_sort_blocks_100epi`](https://huggingface.co/datasets/CoRL2026-CSI/SO101-teleop_sort_blocks_100epi) — 100 episodes, 94,568 frames, 30 fps, human teleop.
+
+## Training
+
+| | |
+|---|---|
+| Hardware | 4 × GPU (DDP, 🤗 Accelerate) |
+| Per-device batch | 32 |
+| Gradient accumulation | 2 |
+| Effective global batch | 256 |
+| Steps | 18,500 (~50 epochs) |
+| Optimizer | AdamW, β=(0.9, 0.95), wd=0.01, grad clip 1.0 |
+| LR | cosine decay, peak 2.5e-5 → 2.5e-6, warmup 1000, decay 30000 |
+| Gradient checkpointing | on |
+| Image aug | ColorJitter (brightness/contrast/saturation/hue), SharpnessJitter, RandomAffine — `max_num=3`, random order |
+| Seed | 1000 |
+
+Training script: [`scripts/train_pi05_sort_blocks.sh`](https://github.com/HyeonseokE/train_with_lerobot/blob/main/scripts/train_pi05_sort_blocks.sh).
+
+## Usage
+
+```python
+from lerobot.policies.pi05.modeling_pi05 import PI05Policy
+
+policy = PI05Policy.from_pretrained("CoRL2026-CSI/pi05_teleop_sort_block").to("cuda").eval()
+```
+
+```bash
+lerobot-eval --policy.path=CoRL2026-CSI/pi05_teleop_sort_block --env.type=<env> --eval.n_episodes=20
+```
+
+## Limitations
+
+- Single task, single seed; no quantitative success rate reported here.
+- Trained on a single-arm SO-101; the right-wrist camera slot is empty.
+- 100 episodes only — sensitive to camera/lighting domain shift.
+
+## License
+
+Apache 2.0 (inherits from [`lerobot/pi05_base`](https://huggingface.co/lerobot/pi05_base)).