Instructions to use poxonit/diffusion_chess_300_test_run_camdrop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use poxonit/diffusion_chess_300_test_run_camdrop with LeRobot:
- Notebooks
- Google Colab
- Kaggle
File size: 836 Bytes
5c1c41f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | {
"checkpoint": "/home/sky/outputs/train/diffusion_chess_300_camdrop/checkpoints/last/pretrained_model",
"dataset_repo": "AnonymousMouse404/chess_300",
"n_eval_episodes": 20,
"eval_episodes": [
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"n_eval_batches": 214,
"n_eval_frames": 6819,
"diffusion_loss": 0.0050743053072318765,
"action_mse": 14.814462722646935,
"action_l1": 1.4622837310022183,
"note": "Offline action-prediction metrics on dataset frames (not closed-loop task success). Evaluated within the trained episode prefix, so this reflects training-set fit rather than held-out generalization. action_mse / action_l1 are in the raw action space (joint positions, degrees)."
} |