| --- |
| license: mit |
| tags: |
| - world-model |
| - dreamerv3 |
| - binary-arithmetic |
| - mechanistic-interpretability |
| --- |
| |
| # A World Model That Learned Perfect Binary Arithmetic |
|
|
| DreamerV3 world model trained on a 4-bit binary counting environment (500K steps). The model learned to simulate carry cascades autonomously — 100% completion rate under full observation ablation. |
|
|
| **Paper**: [GitHub](https://github.com/major-scale/anim-binary-counting) |
|
|
| ## Files |
|
|
| | File | Description | Size | |
| |------|-------------|------| |
| | `latest.pt` | Full DreamerV3 checkpoint (PyTorch) | 136 MB | |
| | `exported/dreamer_weights.bin` | Extracted weight matrices for numpy RSSM | 23 MB | |
| | `exported/dreamer_manifest.json` | Weight name mapping | 4 KB | |
| | `battery.npz` | Pre-collected hidden states from 15 episodes | 25 MB | |
| | `metrics.jsonl` | Training metrics log | 79 KB | |
|
|
| ## Usage |
|
|
| The analysis scripts use the exported weights (no PyTorch required): |
|
|
| ```bash |
| git clone https://github.com/major-scale/anim-binary-counting |
| cd anim-binary-counting |
| |
| # Download exported weights |
| mkdir -p checkpoints/exported |
| wget https://huggingface.co/major-scale/anim-binary-counting/resolve/main/exported/dreamer_weights.bin -O checkpoints/exported/dreamer_weights.bin |
| wget https://huggingface.co/major-scale/anim-binary-counting/resolve/main/exported/dreamer_manifest.json -O checkpoints/exported/dreamer_manifest.json |
| wget https://huggingface.co/major-scale/anim-binary-counting/resolve/main/battery.npz -O data/battery.npz |
| |
| # Run analysis |
| pip install -r code/requirements.txt |
| python code/analysis/verify_dual_mode.py |
| ``` |
|
|
| ## Training |
|
|
| Trained with [DreamerV3-torch](https://github.com/NM512/dreamerv3-torch) on a single GPU (~4 hours). See `code/training/` in the GitHub repo for configs and launcher. |
|
|
| ## License |
|
|
| MIT |
|
|
