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# NEBULA v0.4 - Quick Start Guide |
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**Equipo NEBULA: Francisco Angulo de Lafuente y รngel Vega** |
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## ๐ 5-Minute Quick Start |
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### Step 1: Install Dependencies |
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```bash |
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pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118 |
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pip install pennylane transformers numpy scipy |
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``` |
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### Step 2: Download and Test |
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```python |
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import torch |
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from NEBULA_UNIFIED_v04 import NEBULAUnifiedModel |
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# Initialize model |
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device = 'cuda' if torch.cuda.is_available() else 'cpu' |
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model = NEBULAUnifiedModel(device=device) |
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# Test with random sudoku |
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sudoku = torch.randn(1, 81, device=device) |
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result = model(sudoku) |
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print(f"Photonic neural network working! Output shape: {result['main_output'].shape}") |
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``` |
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### Step 3: Load Pretrained Weights |
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```python |
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# Load validated model |
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model.load_state_dict(torch.load('nebula_photonic_validated_final.pt')) |
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model.eval() |
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print("โ
NEBULA v0.4 ready for spatial reasoning!") |
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``` |
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--- |
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## ๐ก Key Features |
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- **Authentic Photonic Computing**: Real optical physics simulation |
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- **Quantum Memory**: 4-qubit quantum circuits for information storage |
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- **Holographic Memory**: Complex interference patterns for associative memory |
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- **RTX Optimization**: Native GPU acceleration with Tensor Cores |
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--- |
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## ๐ Expected Results |
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- **Spatial Reasoning Accuracy**: ~50% |
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- **Improvement over Random**: +14 percentage points |
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- **Performance**: 89th percentile |
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- **Training Time**: ~15 epochs for convergence |
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--- |
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For complete documentation, see: |
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- [Technical Details](docs/TECHNICAL_DETAILS.md) |
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- [Reproducibility Guide](docs/REPRODUCIBILITY_GUIDE.md) |
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- [Physics Background](docs/PHYSICS_BACKGROUND.md) |
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**"Paso a paso, sin prisa, con calma"** - Project NEBULA Philosophy |