DiffusionMagic

DiffusionMagic is simple to use Stable Diffusion workflows using diffusers. DiffusionMagic focused on the following areas:

• Easy to use
• Cross-platform (Windows/Linux/Mac)
• Modular design, latest best optimizations for speed and memory

What's New?

• Added Stable Diffusion XL support
• Added Controlnet workflows-Canny, MLSD (Line control), Normal, HED, Pose, Depth, Scribble, Segmentation
• Added Pytorch 2.0 support
• Added schedulers - KDPM2 Discrete Scheduler,Heun Discrete Scheduler,KDPM2 Ancestral Discrete Scheduler,DPM Solver Singlestep Scheduler

Run Stable Diffusion XL on Low  VRAM  GPUs (<8GB)

Please read our tutorial  at nolowiz 

Run Stable Diffusion XL on Colab using DiffusionMagic

Please read our tutorial at nolowiz

Features

• Stable diffusion XL
• Supports various Stable Diffusion workflows
  • Text to Image
  • Image to Image
  • Image variations
  • Image Inpainting
  • Depth to Image
  • Instruction-based image editing
• Supports all stable diffusion Hugging Face models
• Supports Stable diffusion v1 and v2 models, derived models
• Works on Windows/Linux/Mac 64-bit
• Works on CPU,GPU( Recent Nvidia GPU),Apple Silicon M1/M2 hardware
• Supports DEIS scheduler for faster image generation (10 steps)
• Supports 7 different samplers with latest DEIS sampler
• LoRA(Low-Rank Adaptation of Large Language Models) models support (~3 MB size)
• Easy to add new diffuser model by updating stable_diffusion_models.txt
• Low VRAM mode supports GPU with RAM < 4 GB
• Fast model loading
• Supports Attention slicing and VAE slicing
• Simple installation using install.bat/install.sh

Please note that AMD GPUs are not supported.

System Requirements:

• Works on Windows/Linux/Mac 64-bit
• Works on CPU,GPU,Apple Silicon M1/M2 hardware
• 12 GB System RAM
• ~11 GB disk space after installation (on SSD for best performance)

How to install and use

Full instruction details are available here https://github.com/rupeshs/diffusionmagic

Windows installation https://github.com/rupeshs/diffusionmagic#how-to-install-and-run-on-windows

Linux installation https://github.com/rupeshs/diffusionmagic#how-to-install-and-run-on-linux