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README.md

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+---
+tags:
+- image-classification
+- cantor-fusion
+- geometric-deep-learning
+- safetensors
+- vision-transformer
+library_name: pytorch
+datasets:
+- cifar10
+- cifar100
+metrics:
+- accuracy
+---
+
+# vit-beans-v3
+
+**Geometric Deep Learning with Cantor Multihead Fusion**
+
+This repository contains multiple training runs using Cantor fusion architecture with pentachoron structures and geometric routing. All models use SafeTensors format for security.
+
+## Repository Structure
+```
+vit-beans-v3/
+├── runs/
+│   ├── cifar10_weighted_TIMESTAMP/
+│   │   ├── checkpoints/
+│   │   │   ├── best_model.safetensors
+│   │   │   ├── best_training_state.pt
+│   │   │   └── best_metadata.json
+│   │   ├── tensorboard/
+│   │   ├── config.yaml
+│   │   └── README.md
+│   ├── cifar100_consciousness_TIMESTAMP/
+│   │   └── ...
+│   └── ...
+└── README.md (this file)
+```
+
+## Current Run
+
+**Latest**: `cifar100_consciousness_20251119_045425`
+- **Dataset**: CIFAR100
+- **Fusion Mode**: consciousness
+- **Architecture**: 6 blocks, 8 heads
+- **Simplex**: 4-simplex (5 vertices)
+
+## Architecture
+
+The Cantor Fusion architecture uses:
+- **Geometric Routing**: Pentachoron (5-simplex) structures for token routing
+- **Cantor Multihead Fusion**: Multiple fusion heads with geometric attention
+- **Beatrix Consciousness Routing**: Optional consciousness-aware token fusion using the Devil's Staircase
+- **SafeTensors Format**: All model weights use SafeTensors (not pickle) for security
+
+## Usage
+
+### Download a Model
+```python
+from huggingface_hub import hf_hub_download
+from safetensors.torch import load_file
+import torch
+
+# Download model weights
+model_path = hf_hub_download(
+    repo_id="AbstractPhil/vit-beans-v3",
+    filename="runs/YOUR_RUN_NAME/checkpoints/best_model.safetensors"
+)
+
+# Load weights (SafeTensors - no pickle!)
+state_dict = load_file(model_path)
+model.load_state_dict(state_dict)
+```
+
+### Browse Runs
+
+Each run directory contains:
+- `checkpoints/` - Model weights (safetensors), training state, metadata
+- `tensorboard/` - TensorBoard logs for visualization
+- `config.yaml` - Complete training configuration
+- `README.md` - Run-specific details and results
+
+## Model Variants
+
+- **Weighted Fusion**: Standard geometric fusion with learned weights
+- **Consciousness Fusion**: Uses Beatrix routing with consciousness emergence
+
+## Citation
+```bibtex
+@misc{vit_beans_v3,
+  author = {AbstractPhil},
+  title = {vit-beans-v3: Geometric Deep Learning with Cantor Fusion},
+  year = {2025},
+  publisher = {HuggingFace},
+  url = {https://huggingface.co/AbstractPhil/vit-beans-v3}
+}
+```
+
+## Training Details
+
+All models trained with:
+- Optimizer: AdamW
+- Mixed Precision: Available on A100
+- Augmentation: AutoAugment (CIFAR10 policy)
+- Format: SafeTensors (ClamAV safe)
+
+Built with geometric consciousness-aware routing using the Devil's Staircase (Beatrix) and pentachoron parameterization.
+
+---
+
+**Repository maintained by**: [@AbstractPhil](https://huggingface.co/AbstractPhil)
+
+**Latest update**: 2025-11-19 04:54:47