automatic
SD.Next: All-in-one for AI generative image
Stars: 5919
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:
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 - Platform specific autodetection and tuning performed on install
- Optimized processing with latest
torch
developments with built-in support for model compile, quantize and compress
Compile backends: Triton | StableFast | DeepCache | OneDiff
Quantization and compression methods: BitsAndBytes | TorchAO | Optimum-Quanto | NNCF - Built-in queue management
- Built in installer with automatic updates and dependency management
- Mobile compatible
Main interface using StandardUI:
Main interface using ModernUI:
For screenshots and informations on other available themes, see Themes
SD.Next supports broad range of models: supported models and model specs
- 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
- Get started with SD.Next by following the installation instructions
- For more details, check out advanced installation guide
- List and explanation of command line arguments
- Install walkthrough video
[!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
- Main credit goes to Automatic1111 WebUI for the original codebase
- Additional credits are listed in Credits
- Licenses for modules are listed in Licenses
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
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