GRASPNET_FINAL_h100

openpi π₀.₅ policy checkpoint.

• Train config: pi05_Franka_GRASPNET_FINAL

• Experiment: GRASPNET_FINAL_h100

• Checkpoints in this repo:

• step_25000/

Each folder is one training step and is self-contained.

• Training dataset: saifahmad123/GRASPNET_FINAL

Contents

Path	Purpose
step_25000/params/	Model weights. Required to serve the policy.
step_25000/assets/	Normalization statistics. Required to serve the policy.
step_25000/train_state/	Optimizer state. Only present if uploaded with --include-train-state; needed to resume training.

Usage

from huggingface_hub import snapshot_download
from openpi.policies import policy_config
from openpi.training import config as _config

ckpt = snapshot_download("saifahmad123/GRASPNET_FINAL_h100", allow_patterns="step_25000/*") + "/step_25000"
train_config = _config.get_config("pi05_Franka_GRASPNET_FINAL")
policy = policy_config.create_trained_policy(train_config, ckpt)

action_chunk = policy.infer(observation)["actions"]