automatic

automatic

SD.Next: All-in-one for AI generative image

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Automatic is an Image Diffusion implementation with advanced features. It supports multiple diffusion models, built-in control for text, image, batch, and video processing, and is compatible with various platforms and backends. The tool offers optimized processing with the latest torch developments, built-in support for torch.compile, and multiple compile backends. It also features platform-specific autodetection, queue management, enterprise-level logging, and a built-in installer with automatic updates and dependency management. Automatic is mobile compatible and provides a main interface using StandardUI and ModernUI.

README:

SD.Next

Image Diffusion implementation with advanced features

Last update License Discord Sponsors

Docs | Wiki | Discord | Changelog

Table of contents

SD.Next Features

All individual features are not listed here, instead check ChangeLog for full list of changes

  • Multiple UIs!
    Standard | Modern
  • Multiple diffusion models!
  • Built-in Control for Text, Image, Batch and video processing!
  • Multiplatform!
    Windows | Linux | MacOS | nVidia | AMD | IntelArc/IPEX | DirectML | OpenVINO | ONNX+Olive | ZLUDA
  • Multiple backends!
    Diffusers | Original
  • Platform specific autodetection and tuning performed on install
  • Optimized processing with latest torch developments with built-in support for torch.compile
    and multiple compile backends: Triton, ZLUDA, StableFast, DeepCache, OpenVINO, NNCF, IPEX, OneDiff
  • Built-in queue management
  • Built in installer with automatic updates and dependency management
  • Mobile compatible

Main interface using StandardUI:
screenshot-standardui

Main interface using ModernUI:

screenshot-modernui

For screenshots and informations on other available themes, see Themes


Model support

SD.Next supports broad range of models: supported models and model specs

Platform support

  • nVidia GPUs using CUDA libraries on both Windows and Linux
  • AMD GPUs using ROCm libraries on Linux
    Support will be extended to Windows once AMD releases ROCm for Windows
  • Intel Arc GPUs using OneAPI with IPEX XPU libraries on both Windows and Linux
  • Any GPU compatible with DirectX on Windows using DirectML libraries
    This includes support for AMD GPUs that are not supported by native ROCm libraries
  • Any GPU or device compatible with OpenVINO libraries on both Windows and Linux
  • Apple M1/M2 on OSX using built-in support in Torch with MPS optimizations
  • ONNX/Olive
  • AMD GPUs on Windows using ZLUDA libraries

Getting started

[!TIP] And for platform specific information, check out
WSL | Intel Arc | DirectML | OpenVINO | ONNX & Olive | ZLUDA | AMD ROCm | MacOS | nVidia | Docker

[!WARNING] If you run into issues, check out troubleshooting and debugging guides

[!TIP] All command line options can also be set via env variable
For example --debug is same as set SD_DEBUG=true

Credits

Evolution

starts

Docs

If you're unsure how to use a feature, best place to start is Docs and if its not there,
check ChangeLog for when feature was first introduced as it will always have a short note on how to use it

Sponsors

Allan GrantBrent Ozara.v.mantzarisSML (See-ming Lee)

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