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amanpandey23/pi05_cloth_folding_v2
pi05_cloth_folding_v2 is a robotics model from amanpandey23. Use it for the robotics task on the model card, and read the license before you ship it in a product. It is set up for orbax-checkpoint. The card lists the license as apache-2.0.
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Updated Nov 7, 2025
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From the Hugging Face model README
Model checkpoint for step 25000.
25000pi05_cloth_folding_v4/home/prakhar-goel/data_farm/checkpoints/pi05/pi05_cloth_folding_v4/25000This checkpoint contains:
params/: Model parameters in JAX/Flax formattrain_state/: Training state including optimizer statesassets/: Normalization statistics and other training assets_CHECKPOINT_METADATA: Checkpoint metadataTo load this checkpoint, use:
from pathlib import Path
import jax
import orbax.checkpoint as ocp
from etils import epath
checkpoint_dir = Path("path/to/downloaded/checkpoint")
# Load parameters
restored = ocp.CheckpointManager(checkpoint_dir).restore(
checkpoint_dir,
items={
"params": ...,
"train_state": ...,
}
)
Or use with OpenPI/LeRobot policy loading:
from openpi.policies.policy_config import create_trained_policy
# Load policy from checkpoint
policy = create_trained_policy(
train_config=your_config,
checkpoint_dir=str(checkpoint_dir)
)
{
"item_handlers": {
"assets": "openpi.training.checkpoints.CallbackHandler",
"params": "orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler",
"train_state": "orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler"
},
"metrics": {},
"performance_metrics": {},
"init_timestamp_nsecs": 1762495032653103749,
"commit_timestamp_nsecs": 1762495109617216108,
"custom_metadata": {}
}