g1-inspire-redball-n16
GR00T N1.6 fine-tune for the red-ball pick-and-place task on a Unitree G1
with Inspire hands. Trained on 76 teleop episodes (IsaacLab, 424×240
ego_view, 34-frame chunks at 60 Hz).
This is the N1.6 counterpart of birbirll/g1-inspire-redball-n17, trained with the same recipe as birbirll/g1-inspire-piston-n16: effective batch 32 (8×4 accumulation), 10k steps, lr 1e-4 cosine, state_dropout 0.8, color jitter, paged_adamw_8bit + gradient checkpointing (fits a 24 GB GPU). Final train loss 0.016.
Serving
Serve this repository root directly — processor_config.json and both
model shards live at the root (do not point at a checkpoint-N subdir):
python gr00t/eval/run_gr00t_server.py \
--model_path <path-to-this-repo> \
--embodiment_tag NEW_EMBODIMENT --port 5555
Serving rules that matter:
- Embodiment tag is
NEW_EMBODIMENT(notUNITREE_G1). - Low-rate serving: run the client at
inference_hz 1.25(chunked, no temporal ensembling). N1.6 checkpoints from this recipe under-commit when replanned faster with ensembling. - Camera input: 424×240
ego_view, raw passthrough — the server resizes via its own processor config (shortest_image_edge=256). - Action layout (30-D): 14 arm joints, 12 Inspire hand joints, base_height, 3-D navigate command. State 63-D (arms, hands, waist, tactile — tactile unused by the model).
Status
- Open-loop replay against the training data: verified.
- Closed-loop in MuJoCo: carries without grasp (visual domain differs from the IsaacLab training render); closed-loop in the training render: grasp triggers.
- Real-robot deployment: wiring validated on a hardware-free bench; behavior on hardware not yet evaluated.