SD.Next

DESOTA Implementation

Stable Diffusion implementation with advanced features, installable directly from DeSOTA DMT

Wiki | Discord | Changelog

Notable features

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

• Multiple backends!
  ▹ Original | Diffusers
• Multiple diffusion models!
  ▹ Stable Diffusion 1.5/2.1 | SD-XL | LCM | Segmind | Kandinsky | Pixart-α | Würstchen | aMUSEd | DeepFloyd IF | UniDiffusion | SD-Distilled | BLiP Diffusion | etc.
• Built-in Control for Text, Image, Batch and video processing!
  ▹ ControlNet | ControlNet XS | Control LLLite | T2I Adapters | IP Adapters
• Multiplatform!
  ▹ Windows | Linux | MacOS with CPU | nVidia | AMD | IntelArc | DirectML | OpenVINO | ONNX+Olive
• 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
• Improved prompt parser
• Enhanced Lora/LoCon/Lyco code supporting latest trends in training
• Built-in queue management
• Enterprise level logging and hardened API
• Modern localization and hints engine
• Broad compatibility with existing extensions ecosystem and new extensions manager
• Built in installer with automatic updates and dependency management
• Modernized UI with theme support and number of built-in themes (dark and light)

Backend support

SD.Next supports two main backends: Original and Diffusers:

• Original: Based on LDM reference implementation and significantly expanded on by A1111
  This is the default backend and it is fully compatible with all existing functionality and extensions
  Supports SD 1.x and SD 2.x models
  All other model types such as SD-XL, LCM, PixArt, Segmind, Kandinsky, etc. require backend Diffusers
• Diffusers: Based on new Huggingface Diffusers implementation
  Supports original SD models as well as all models listed below
  See wiki article for more information

Model support

Additional models will be added as they become available and there is public interest in them

• RunwayML Stable Diffusion 1.x and 2.x (all variants)
• StabilityAI Stable Diffusion XL
• StabilityAI Stable Video Diffusion Base and XT
• LCM: Latent Consistency Models
• aMUSEd 256 256 and 512
• Segmind Vega
• Segmind SSD-1B
• Kandinsky 2.1 and 2.2 and latest 3.0
• PixArt-α XL 2 Medium and Large
• Warp Wuerstchen
• Playground v1, v2 256, v2 512, v2 1024
• Tsinghua UniDiffusion
• DeepFloyd IF Medium and Large
• ModelScope T2V
• Segmind SD Distilled (all variants)
• BLIP-Diffusion

Also supported are modifiers such as:

• LCM and Turbo (Adversarial Diffusion Distillation) networks
• All LoRA types such as LoCon, LyCORIS, HADA, IA3, Lokr, OFT
• AnimateDiff for SD 1.5
• IP-Adapters for SD 1.5 and SD-XL

Important

• Loading any model other than standard SD 1.x / SD 2.x requires use of backend Diffusers
• Loading any other models using Original backend is not supported
• Loading manually download model .safetensors files is supported for SD 1.x / SD 2.x / SD-XL models only
• For all other model types, use backend Diffusers and use built in Model downloader or
  select model from Networks -> Models -> Reference list in which case it will be auto-downloaded and loaded

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 (experimental)

Install

• Step-by-step install guide
• Advanced install notes
• Common installation errors
• FAQ
• If you can't run us locally, try our friends at RunDuffusion!

Tip

• Server can run without virtual environment,
  Recommended to use VENV to avoid library version conflicts with other applications
• nVidia/CUDA / AMD/ROCm / Intel/OneAPI are auto-detected if present and available,
  For any other use case such as DirectML, ONNX/Olive, OpenVINO 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

Run

Once SD.Next is installed, simply run webui.ps1 or webui.bat (Windows) or webui.sh (Linux or MacOS)

Below is partial list of all available parameters, run webui --help for the full list:

Server options:
  --config CONFIG                  Use specific server configuration file, default: config.json
  --ui-config UI_CONFIG            Use specific UI configuration file, default: ui-config.json
  --medvram                        Split model stages and keep only active part in VRAM, default: False
  --lowvram                        Split model components and keep only active part in VRAM, default: False
  --ckpt CKPT                      Path to model checkpoint to load immediately, default: None
  --vae VAE                        Path to VAE checkpoint to load immediately, default: None
  --data-dir DATA_DIR              Base path where all user data is stored, default:
  --models-dir MODELS_DIR          Base path where all models are stored, default: models
  --share                          Enable UI accessible through Gradio site, default: False
  --insecure                       Enable extensions tab regardless of other options, default: False
  --listen                         Launch web server using public IP address, default: False
  --auth AUTH                      Set access authentication like "user:pwd,user:pwd""
  --autolaunch                     Open the UI URL in the system's default browser upon launch
  --docs                           Mount Gradio docs at /docs, default: False
  --no-hashing                     Disable hashing of checkpoints, default: False
  --no-metadata                    Disable reading of metadata from models, default: False
  --no-download                    Disable download of default model, default: False
  --backend {original,diffusers}   force model pipeline type

Setup options:
  --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
  --requirements                   Force re-check of requirements, default: False
  --quick                          Run with startup sequence only, default: False
  --use-directml                   Use DirectML if no compatible GPU is detected, default: False
  --use-openvino                   Use Intel OpenVINO backend, default: False
  --use-ipex                       Force use Intel OneAPI XPU backend, default: False
  --use-cuda                       Force use nVidia CUDA backend, default: False
  --use-rocm                       Force use AMD ROCm backend, default: False
  --use-xformers                   Force use xFormers cross-optimization, 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
  --skip-all                       Skips running all checks, default: False
  --experimental                   Allow unsupported versions of libraries, default: False
  --reinstall                      Force reinstallation of all requirements, default: False
  --safe                           Run in safe mode with no user extensions

Notes

Extensions

SD.Next comes with several extensions pre-installed:

• ControlNet
• Agent Scheduler
• Image Browser

Collab

• We'd love to have additional maintainers with full admin rights. If you're interested, ping us!
• 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 we'd really love to have additional contributors and/or maintainers to join and help lead the efforts on different platforms.

Goals

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.

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".

General goals:

• Multi-model
  • Enable usage of as many as possible txt2img and img2img generative models
• 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

Docs

If you're unsure how to use a feature, best place to start is Wiki 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

• Wiki
• ReadMe
• ToDo
• ChangeLog
• CLI Tools

Sponsors