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README.md

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+---
+license: apache-2.0
+tags:
+  - robotics
+  - vla
+  - openpi
+  - pi05
+  - forcesight
+  - tactile
+---
+
+# ForceSight — pi0.5 fine-tuned checkpoints
+
+Fine-tuned pi0.5 (openpi) policies for ForceSight manipulation tasks.
+All checkpoints are from step 20000, trained on 6/3 data.
+
+## Checkpoints
+
+| Folder | Variant | Description |
+|--------|---------|-------------|
+| `pi05_6_3/` | Baseline pi0.5 | Vanilla pi0.5 fine-tune, no tactile. |
+| `encoder_6_3/` | pi0.5 + tactile encoder | Conv-Based encoder for tactile images |
+| `tactile_6_3/` | pi0.5 + tactile | Tactile images are augmented as camera inputs to the VLA model |
+
+Each folder contains `params/` (orbax weights) and `assets/` (normalization stats — required for inference).
+
+## Setup
+
+- **Base model:** pi0.5 (openpi)
+- **Robot:** Franka Emika Panda + Franka Hand
+- **Tasks:** Medicine, Balance, Gear Insertion, Plug Insertion. 
+- **Training:** 20000 steps, 4 A6000 GPUs.
+
+## Loading
+
+Download a single checkpoint:
+
+```bash
+hf download mlshehab/forcesight --include "pi05_6_3/*" --local-dir ./forcesight
+```
+
+Load with openpi:
+
+```python
+from openpi.policies import policy_config
+from openpi.training import config
+
+cfg = config.get_config("<FILL IN: config name, e.g. pi05_forcesight>")
+policy = policy_config.create_trained_policy(cfg, "./forcesight/pi05_6_3")
+```
+
+> Note: the tactile variants require a custom openpi config/fork. See [openpi](https://github.com/Physical-Intelligence/openpi).