| --- |
| license: mit |
| library_name: pytorch |
| tags: |
| - rubiks-cube |
| - reinforcement-learning |
| - deepcubea |
| - pytorch |
| pipeline_tag: other |
| --- |
| |
| # DeepCube — Cube3 (3×3×3) cost-to-go network |
|
|
| PyTorch weights for a DeepCubeA-style cost-to-go network that solves the 3×3×3 Rubik's cube via weighted A\*. |
| |
| - **Input**: one-hot encoded cube state (324 dims = 54 stickers × 6 colors) |
| - **Output**: scalar cost-to-go estimate (predicted moves to solved state) |
| - **Architecture**: MLP — see `deepcube/model.py` in the source repo |
| - **Training**: Approximate Value Iteration on random scrambles (see `train.ipynb`) |
| - **Source code**: https://github.com/ac1982/deepcube |
| |
| ## Files |
| |
| - `deepcube_cube3.pt` — final weights (keys: `net`, `cfg`, `loss_hist`, `elapsed`) |
| |
| ## Usage |
| |
| ```python |
| from huggingface_hub import hf_hub_download |
| from deepcube.model import load_checkpoint |
| |
| ckpt_path = hf_hub_download("alexever/deepcube-cube3", "deepcube_cube3.pt") |
| model, cfg = load_checkpoint(ckpt_path) |
| ``` |
| |
| Or via the bundled server, which auto-loads from `checkpoints/deepcube_cube3.pt`: |
| |
| ```bash |
| huggingface-cli download alexever/deepcube-cube3 deepcube_cube3.pt \ |
| --local-dir checkpoints |
| python -m deepcube.server |
| ``` |
| |
| ## License |
| |
| MIT — see source repository. |
| |
