mjoshs's picture
Upload README.md with huggingface_hub
aa80a6e verified
---
title: Silicon Photonics Image Generator
emoji: 🔬
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: "4.44.0"
app_file: app.py
pinned: false
license: mit
---
# 🔬 Silicon Photonics Image Generator
Generate technical diagrams and visualizations for silicon photonics using our fine-tuned LoRA model based on Stable Diffusion XL.
## Features
- **High-Quality Generation**: Uses Stable Diffusion XL with custom LoRA fine-tuning
- **Technical Focus**: Optimized for silicon photonics diagrams and visualizations
- **Customizable Parameters**: Control inference steps, guidance scale, dimensions, and seed
- **Professional Output**: Generates technical diagrams suitable for educational and research purposes
## Usage
1. Enter a detailed prompt describing the silicon photonics component you want to visualize
2. Adjust the negative prompt to exclude unwanted elements
3. Fine-tune the generation parameters:
- **Inference Steps**: Higher values (20-30) for better quality
- **Guidance Scale**: Controls adherence to prompt (7.0 is recommended)
- **Dimensions**: Choose appropriate size for your use case
- **Seed**: Use the same seed for reproducible results
4. Click "Generate Image" to create your visualization
## Example Prompts
- "A detailed technical diagram of a silicon waveguide showing light propagation"
- "Cross-section view of a silicon photonic integrated circuit with waveguides and couplers"
- "3D visualization of a silicon ring resonator for optical filtering"
- "Schematic diagram of a silicon photonic modulator with electrodes"
## Model Details
- **Base Model**: Stable Diffusion XL 1.0
- **Fine-tuning**: LoRA (Low-Rank Adaptation) for silicon photonics
- **Training Data**: Technical diagrams and visualizations from silicon photonics literature
- **Optimized For**: Educational content, research visualizations, technical documentation
## Technical Specifications
- **Framework**: PyTorch with Diffusers
- **Precision**: FP16 for efficiency
- **Device**: CUDA (if available) or CPU
- **Memory**: ~8GB VRAM recommended for optimal performance
## License
This model is fine-tuned for educational and research purposes in silicon photonics.