Stable Diffusion implementation

This project aims to create a custom implementation of the stable diffusion technique for generating high-quality images from text prompts. Stable Diffusion is a generative model that iteratively refines noise into a coherent image based on the given text input.

Implemented Components

• ✅ VAE (Variational Autoencoder)
• ✅ CLIP (Contrastive Language–Image Pretraining)
• ✅ Attention Mechanism
• ✅ Time Embedding
• ✅ Attention UNet is in progress
• ❌ Denoising Algorithm
• ❌ Full Pipeline