Lilly Tech Systems
Learn Stable Diffusion
Master the most powerful open-source AI image generation model. Create stunning images from text prompts, fine-tune custom models, and use advanced techniques like ControlNet, img2img, and inpainting.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
What is Stable Diffusion? Explore SD 1.5, SDXL, SD3, and how it started the open-source AI image generation revolution.
2. How It Works
Understand the diffusion process, U-Net architecture, VAE, CLIP text encoder, and latent space representation.
3. Prompt Craft
Master positive and negative prompts, weight syntax, style keywords, composition techniques, and proven prompt formulas.
4. ControlNet
Guide image generation with ControlNet types: canny edges, depth maps, pose detection. Plus img2img, inpainting, and outpainting.
5. Fine-tuning
Train custom models with DreamBooth, LoRA, and textual inversion. Create personalized styles and characters.
6. Tools & UIs
Compare ComfyUI, Automatic1111, InvokeAI, Fooocus, and the diffusers Python library for running Stable Diffusion.
7. Best Practices
Optimization tips, hardware requirements, ethical considerations, and common troubleshooting solutions.
What You'll Learn
By the end of this course, you'll be able to:
Generate AI Art
Create stunning images from text descriptions using various Stable Diffusion models and techniques.
Train Custom Models
Fine-tune models on your own images using DreamBooth and LoRA for personalized generation.
Control Generation
Use ControlNet, img2img, and inpainting to precisely guide the AI output to match your vision.
Use Professional Tools
Set up and use ComfyUI, Automatic1111, and the diffusers library for production workflows.