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giakhuyendihoc/k6_pour_full
k6_pour_full is a robotics model from giakhuyendihoc. 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 openpi.
Full fine-tuned UR5 OpenPI/Pi0.5 policy checkpoint for the k6pourfull deployment preset.
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Updated Jul 5, 2026
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From the Hugging Face model README
Full fine-tuned UR5 OpenPI/Pi0.5 policy checkpoint for the k6_pour_full deployment preset.
This upload contains all available inference checkpoint steps from the local run: 10000, 20000, 30000.
The optimizer state is intentionally not uploaded by default because it is not needed for inference and is much larger than the model weights. Set UPLOAD_OPTIMIZER=1 when running the uploader if optimizer states are really needed.
checkpoints/<step>/model.safetensors: PyTorch model weights for each uploaded step.checkpoints/<step>/metadata.pt: original checkpoint metadata from training.checkpoints/<step>/metadata.json: JSON-readable metadata summary for each step.checkpoints/<step>/assets/norm_stats.json: normalization stats used for inference.assets/norm_stats.json: normalization stats used for inference.configs/deployment.env: deployment preset used in vla_ur5.configs/*.py and configs/*.sh: source/config snapshots needed to reproduce training/inference wiring.pi05_ww_k6_pour_tcp240_noforce_full_5090WW-k610000, 20000, 30000300005010giakhuyendihoc/ur5_pour_full_tcp240_noforce8.807756561570697Prompt:
Pick the black and white container, place it on top of the black and red container, then pick the blue container with nuts and metal plate inside and pour the nuts and metal plate inside the black and red container until the blue container is empty
Use the local vla_ur5 / OpenPI deployment code:
TASK=k6_pour_full bash deployment/scripts/serve_policy.sh
When loading directly from this HF repo, use checkpoints/30000 as the checkpoint directory for the default final model.
The matching config name is:
pi05_ww_k6_pour_tcp240_noforce_full_5090
The config snapshots are included so other users can reconstruct the architecture and transforms even if the local repository evolves.