Robotics
LeRobot
Safetensors
pi0_5
pi05
manipulation
block-transfer
trossen-ai

pi0.5 — Block Transfer (batch size 32)

Fine-tuned pi0.5 vision-language-action policy for the block transfer task on the Trossen AI Stationary bimanual platform.

Model details

Architecture pi0.5 (PaliGemma gemma_2b backbone + gemma_300m action expert)
Base model lerobot/pi05_base
Framework LeRobot
Robot platform Trossen AI Stationary (bimanual, 14-DoF)
Cameras cam_high, cam_low, cam_left_wrist, cam_right_wrist (480×640 RGB)
Action chunk 50 steps, 10 inference steps
Precision bfloat16
License Apache 2.0

Training

Hyperparameter Value
Batch size 32
Training steps 100,000
Learning rate 2e-5 (cosine decay to 2.5e-6 over 30k steps, 1k warmup)
Optimizer AdamW (β=(0.9, 0.95), wd=0.01, grad clip 1.0)
Gradient checkpointing Enabled
Hardware 1× NVIDIA H200 (141 GB VRAM) via Trossen Cloud Service
Dataset TrossenRoboticsCommunity/trossen_ai_stationary_block_transfer

Usage

Load the policy with LeRobot:

from lerobot.policies.pi0_5.modeling_pi0_5 import PI05Policy

policy = PI05Policy.from_pretrained(
    "TrossenRoboticsCommunity/pi05-block-transfer-bs32"
)

See the LeRobot pi0.5 docs for the full inference / rollout setup on real hardware.

Files

File Purpose
config.json Policy configuration
model.safetensors Model weights (~7.5 GB)
policy_preprocessor.json + *_normalizer_processor.safetensors Input normalizer (state/action quantiles)
policy_postprocessor.json + *_unnormalizer_processor.safetensors Output unnormalizer

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