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| cli | ||
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| CHANGELOG.md | ||
| LICENSE.txt | ||
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| installer.py | ||
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README.md
This project started as a fork from Automatic1111 WebUI and it grew significantly since then, but although it diverged considerably, any substantial features to original work is ported to this repository as well.
Top-10 Differentiators
All Individual features are not listed here, instead check Changelog for full list of changes.
- Optimized processingwith latest torch developments
Including built-in support fortorch.compile - Support for multiple backends:
diffusersas well as standardldmbackend - Fully multiplatform with platform specific autodetection and tuning performed on install
- Improved prompt parser
- Enhanced Lora/Locon/Lyco code supporting latest trends in training
- Built-in queue management
- Advanced metadata caching and handling to speed up operations
- Enterprise level logging and hardened API
- Modern localization and hints engine
- Broad compatibility with extisting extensions ecosystem and new extensions manager
- Built in installer with automatic updates and dependency management
- Modernized UI (still based on Gradio) with theme support
Model support
Additional models will be added as they become available and there is public interest in them
- Stable Diffusion 1.x and 2.x including all variants
- Stable Diffusion XL
- Kandinsky 2.1
- DeepFloyd IF
- UniDiffusion
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 - Any GPU compatibile with DirectX on Windows using DirectML libraries.
This includes support for AMD GPUs that are not supported by native ROCm libraries - Intel Arc GPUs using Intel OneAPI Ipex/XPU libraries
- Apple M1/M2 on OSX using built-in support in Torch with MPS optimizations
Install
- Install first:
Python & Git - Clone repository
git clone https://github.com/vladmandic/automatic - Run launcher
webui.batorwebui.sh:- Platform specific wrapper scripts For Windows, Linux and OSX
- Starts
sdnext.pyin a Python virtual environment (venv) - Uses
install.pyto handle all actual requirements and dependencies
Common Problems
Installation Notes
- Server can run without virtual environment,
but it is recommended to use it to avoid library version conflicts with other applications - nVidia/CUDA and AMD/ROCm are auto-detected is present and available,
but for any other use case specify required parameter explicitly or wrong packages may be installed
as installer will assume CPU-only environment - Full startup sequence is logged in
sdnext.log, so if you encounter any issues, please check it first
Below is partial list of all available parameters, run webui --help for the full list:
Setup options:
--use-ipex Use Intel OneAPI XPU backend, default: False
--use-directml Use DirectML if no compatible GPU is detected, default: False
--use-cuda Force use nVidia CUDA backend, default: False
--use-rocm Force use AMD ROCm backend, default: False
--skip-update Skip update of extensions and submodules, default: False
--skip-requirements Skips checking and installing requirements, default: False
--skip-extensions Skips running individual extension installers, default: False
--skip-git Skips running all GIT operations, default: False
--skip-torch Skips running Torch checks, default: False
--reinstall Force reinstallation of all requirements, default: False
--debug Run installer with debug logging, default: False
--reset Reset main repository to latest version, default: False
--upgrade Upgrade main repository to latest version, default: False
--safe Run in safe mode with no user extensions
Notes
Extensions
SD.Next comes with several extensions pre-installed:
- Dynamic Thresholding
- ControlNet
- Agent Scheduler
- Multi-Diffusion Tiled Diffusion and VAE
- LyCORIS
- Image Browser
- CLiP Interrogator
- Rembg Background Removal
Collab
- To avoid having this repo rely just on me, I'd love to have additional maintainers with full admin rights. If you're interested, ping me!
- In addition to general cross-platform code, desire is to have a lead for each of the main platforms. This should be fully cross-platform, but I would really love to have additional contibutors and/or maintainers to join and help lead the efforts on different platforms.
Goals
The idea behind the fork is to enable latest technologies and advances in text-to-image generation.
Sometimes this is not the same as "as simple as possible to use".
If you are looking an amazing simple-to-use Stable Diffusion tool, I'd suggest InvokeAI specifically due to its automated installer and ease of use.
General goals:
- Cross-platform
- Create uniform experience while automatically managing any platform specific differences
- Performance
- Enable best possible performance on all platforms
- Ease-of-Use
- Automatically handle all requirements, dependencies, flags regardless of platform
- Integrate all best options for uniform out-of-the-box experience without the need to tweak anything manually
- Look-and-Feel
- Create modern, intuitive and clean UI
- Up-to-Date
- Keep code up to date with latest advanced in text-to-image generation
Credits
- Main credit goes to Automatic1111 WebUI
- Additional credits are listed in Credits
- Licenses for modules are listed in Licenses
