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mkpongm/
gr00t-n1_5-sponge-marker-delta-10k

Name: gr00t-n1_5-sponge-marker-delta-10k
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gr00t N1.5 sponge-marker - DELTA actions (step 10000)

Joints are DELTA; gripper is ABSOLUTE. Action norm: mean_std (joints) + min_max (gripper). Recipe: freeze-LLM (tune_llm=False, visual/projector/diffusion tuned), batch 32, 30k steps, decord video backend.

Serving (REQUIRED)

This checkpoint cannot be served with the absolute config - doing so emits raw deltas as absolute joint targets (measured error up to 65 degrees). Copy so101_delta_configs.py to the gr00t repo root (that is the only file needed), then:

bash

python scripts/inference_service.py --server \
  --model-path mkpongm/gr00t-n1_5-sponge-marker-delta-10k \
  --data-config so101_delta_configs:So101SpongeMarkerDeltaDataConfig \
  --embodiment-tag new_embodiment --denoising-steps 8 --port 5556

Normalization stats are read from this checkpoint's experiment_cfg/metadata.json like any other gr00t config - no side-car stats file is needed. action.single_arm holds delta stats (mean ~= [0.12,-1.63,-2.36,-0.54,0.02]); action.gripper and state.* hold absolute stats. The client (eval_lerobot.py) needs no changes - unapply restores absolute joint targets.