YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

GR00T N1.7 Unitree G1 SONIC Deploy Checkpoint

This is the deploy-only export of:

checkpoints/gr00t_n17_g1_sonic/grab_bottle_v2_4gpu_bs64_10k/checkpoint-10000

Resume-training artifacts such as optimizer state, RNG state, scheduler state, trainer state, and training-only configs are intentionally not included here.

Included Files

config.json
model.safetensors.index.json
model-00001-of-00002.safetensors
model-00002-of-00002.safetensors
processor_config.json
statistics.json
embodiment_id.json
experiment_cfg/final_model_config.json
experiment_cfg/final_processor_config.json
experiment_cfg/dataset_statistics.json

Training Summary

  • Base model: nvidia/GR00T-N1.7-3B
  • Embodiment: unitree_g1_sonic / UNITREE_G1_SONIC
  • Dataset: cloudwalk-research/gr00t-g1-grab-bottle-right-hand-v2
  • Task: Unitree G1 right-hand bottle grasp
  • Max steps: 10,000
  • Precision: bf16
  • Action keys: motion_token, left_hand_joints, right_hand_joints

Evaluation Summary

Open-loop checkpoint-10000 result:

  • Avg MSE: 0.00029590
  • Avg MAE: 0.01039191

MuJoCo / SONIC simulation result with lower body locked:

  • Single bottle, grab bottle: 5 / 10 success
  • Bottle + red apple, grab bottle: 3 / 10 success
  • Bottle + red apple, grab red apple: 1 / 10 success
  • Aggregate: 9 / 30 success

Real Unitree G1 deployment was not performed. The reported deployment success rates are simulation results only.

Usage

Load this directory as the GR00T policy checkpoint for SONIC VLA inference:

python gr00t/eval/service.py \
  --model-path /path/to/deploy_checkpoint_10000 \
  --embodiment-tag UNITREE_G1_SONIC \
  --server
Downloads last month
35
Safetensors
Model size
3B params
Tensor type
BF16
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support