SDConcepts / QUICKSTART.md
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A newer version of the Gradio SDK is available: 6.4.0

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Quick Start Guide - Local Testing

Installation Complete! βœ…

All dependencies have been installed successfully. Here's what to do next:

Running the App

Option 1: Simple Run

python app.py

The app will start and show you a URL like:

Running on local URL:  http://127.0.0.1:7860

Open that URL in your browser!

Option 2: Share Publicly (Temporary)

# Edit app.py, change the last line to:
demo.launch(share=True)

This creates a temporary public URL you can share with others.

What to Expect

First Run

  • The app will download the Stable Diffusion model (~4GB)
  • This happens only once - subsequent runs are fast
  • Download location: ~/.cache/huggingface/

Performance

  • With GPU (CUDA): ~10-15 seconds per image
  • Without GPU (CPU): ~2-3 minutes per image

Check if CUDA is available:

python -c "import torch; print(f'CUDA available: {torch.cuda.is_available()}')"

Using the App

Single Style Tab

  1. Enter a prompt (use <style> as placeholder)
    • Example: "a portrait of a warrior in <style>"
  2. Select a style from dropdown
  3. Set seed (e.g., 42)
  4. Click "Generate Image"

Compare All Styles Tab

  1. Enter a prompt with <style> placeholder
  2. Set base seed (e.g., 100)
  3. Click "Generate All Styles"
  4. See all 5 styles side-by-side!

Troubleshooting

"Out of Memory" Error

  • Reduce inference steps to 20-30
  • Close other GPU applications
  • Use CPU mode (slower but works)

Slow Generation

  • This is normal on CPU
  • Consider using GPU for faster results
  • Reduce inference steps for speed

Model Download Fails

  • Check internet connection
  • Ensure ~5GB free disk space
  • Try again - downloads resume automatically

Next Steps

  1. βœ… Test the app locally
  2. βœ… Try different prompts and styles
  3. βœ… Deploy to Hugging Face Spaces (see DEPLOYMENT_GUIDE.md)

Enjoy your Stable Diffusion Style Explorer! 🎨