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ByteMelodist/pi05_allslot_st3
pi05_allslot_st3 is a robotics model from ByteMelodist. 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 lerobot. The card lists the license as apache-2.0.
Pi0.5 (pi05, the LeRobot/openpi port) policy checkpoint for EBiM Task 2 — Deformable Material Handling (Thermal Pad Placement).
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From the Hugging Face model README
Pi0.5 (pi05, the LeRobot/openpi port) policy checkpoint for EBiM Task 2 —
Deformable Material Handling (Thermal Pad Placement).
pi05 (paligemma_variant gemma_2b, action_expert
gemma_300m, bfloat16, chunk_size 50, n_action_steps 50,
num_inference_steps 10).lerobot/pi05_base
(pretrained_path in config.json).local/task2_allslot_st3_s29), recorded with the
benchmark's own LeRobot recorder (30 fps, eval_split 0.05, pyav backend).spine.height.target (see action_feature_names in
config.json).observation.images.base_0_rgb, observation.images.left_wrist_0_rgb,
observation.images.right_wrist_0_rgb. STATE/ACTION normalization:
QUANTILES (pre/post processor pipelines are shipped beside the weights and
must be loaded with them).pi05 policy — point the deployment config's vla.checkpoint at this
directory (see the submission repo's "Fine-tuning on this task's own
demonstrations" / LeRobotBackend, which loads the processor pipelines
saved beside the weights so inference normalization is identical to
training).| file | role |
|---|---|
config.json | pi05 policy config (features, variants, sampling) |
model.safetensors | weights (9 354 050 752 bytes, md5 a437bf0c8669061923d4cfb4493a420f) |
policy_preprocessor.json + policy_preprocessor_step_3_normalizer_processor.safetensors | input pipeline (quantile normalizer) |
policy_postprocessor.json + policy_postprocessor_step_0_unnormalizer_processor.safetensors | output pipeline (unnormalizer) |
train_config.json | full training configuration for reproducibility |