--- library_name: pytorch license: apache-2.0 tags: - vision - image-classification - geometric-deep-learning - vit - cantor-routing - pentachoron - multi-scale --- # 🫘💎 DavidBeans: Unified Vision-to-Crystal Architecture This repository contains training runs for DavidBeans - a unified geometric deep learning architecture combining: - **BEANS (ViT Backbone)**: Cantor-routed sparse attention - **DAVID (Classifier)**: Multi-scale crystal projection with Cayley-Menger geometric regularization ## Repository Structure ``` AbstractPhil/geovit-david-beans/ ├── README.md (this file) └── weights/ ├── run_001_baseline_YYYYMMDD_HHMMSS/ │ ├── best.safetensors │ ├── epoch_010.safetensors │ ├── config.json │ ├── training_config.json │ └── tensorboard/ ├── run_002_5expert_5scale_YYYYMMDD_HHMMSS/ │ └── ... └── ... ``` ## Usage ```python from safetensors.torch import load_file from david_beans import DavidBeans, DavidBeansConfig import json # Pick a run run_path = "weights/run_002_5expert_5scale_20251129_171229" # Load config with open(f"{run_path}/config.json") as f: config_dict = json.load(f) config = DavidBeansConfig(**config_dict) # Load model model = DavidBeans(config) state_dict = load_file(f"{run_path}/best.safetensors") model.load_state_dict(state_dict) # Inference model.eval() with torch.no_grad(): output = model(images) predictions = output['logits'].argmax(dim=-1) ``` ## Training Runs | Run | Name | Accuracy | Notes | |-----|------|----------|-------| | 001 | baseline | 70.05% | Initial CIFAR-100 run | | 002 | 5expert_5scale | 68.34% | 5 experts, 5 scales | ## Architecture ``` Image [B, 3, 32, 32] │ ▼ ┌─────────────────────────────────────────┐ │ BEANS BACKBONE │ │ ├─ Patch Embed → [64 patches, dim] │ │ ├─ Hybrid Cantor Router │ │ ├─ N × Attention Blocks │ │ └─ N × Pentachoron Expert Layers │ └─────────────────────────────────────────┘ │ ▼ ┌─────────────────────────────────────────┐ │ DAVID HEAD │ │ ├─ Multi-scale projection │ │ ├─ Per-scale Crystal Heads │ │ └─ Geometric Fusion │ └─────────────────────────────────────────┘ │ ▼ [num_classes] ``` ## License Apache 2.0