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TrossenRoboticsCommunity/
pi0-block-transfer-trossen-ai-openpi

Name: pi0-block-transfer-trossen-ai-openpi
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pi0-block-transfer-trossen-ai

A π₀ (pi0) policy fine-tuned with openpi (Physical Intelligence's JAX trainer) for the block transfer task on the Trossen AI Stationary bimanual platform.

Framework: openpi (JAX/XLA) — this is not a LeRobot/PyTorch checkpoint. Load it with the openpi runtime, not lerobot.

Inputs

Dataset: TrossenRoboticsCommunity/trossen_ai_stationary_block_transfer — LeRobot v2 format (openpi requires v2; v3 is rejected).
Base model: π₀ (pi0) pretrained checkpoint from Physical Intelligence, LoRA fine-tuned.
Training code: TrossenRobotics/openpi
Hardware: Trossen AI Stationary (bimanual), trained locally on an RTX 5090.
Action/state space: 32-dim (per assets/trossen/norm_stats.json).

Configuration

Steps: 100,000
Batch size: 8
Fine-tuning: LoRA
Norm stats: assets/trossen/norm_stats.json (auto-computed at train time).

How it was trained

Fine-tuned locally on an RTX 5090 using the openpi JAX trainer (LoRA, batch size 8, 100K steps). openpi's first-class π implementation generally outperforms LeRobot's PyTorch π policies. Exported as the final orbax checkpoint (params/ = weights, train_state/ = optimizer state for resuming).

How to use

bash

git clone https://github.com/TrossenRobotics/openpi
# follow openpi serving/inference instructions; point the policy at this repo's params/
# recommended inference rate: 50 Hz

TrossenRoboticsCommunity/
pi0-block-transfer-trossen-ai-openpi

pi0-block-transfer-trossen-ai

Inputs

Configuration

How it was trained

How to use

Outputs

Evaluation

Versions

TrossenRoboticsCommunity/pi0-block-transfer-trossen-ai-openpi

pi0-block-transfer-trossen-ai

Inputs

Configuration

How it was trained

How to use

Outputs

Evaluation

Versions

TrossenRoboticsCommunity/
pi0-block-transfer-trossen-ai-openpi