Install and Run on NVidia GPUs

Automatic Installation

Windows

Install Python 3.10.6 (ticking Add to PATH), and git
Open cmd and type git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui
Double click webui-user.bat

See Troubleshooting section for what to do if things go wrong.

Powershell

Alternatively, here are 2 launch scripts for using powershell:

Scripts (Click to show)

webui.ps1

if ($env:PYTHON -eq "" -or $env:PYTHON -eq $null) {
    $PYTHON = "Python.exe"
} else {
    $PYTHON = $env:PYTHON
}

if ($env:VENV_DIR -eq "" -or $env:VENV_DIR -eq $null) {
    $VENV_DIR = "$PSScriptRoot\venv"
} else {
    $VENV_DIR = $env:VENV_DIR
}

if ($env:LAUNCH_SCRIPT -eq "" -or $env:LAUNCH_SCRIPT -eq $null) {
    $LAUNCH_SCRIPT = "$PSScriptRoot\launch.py"
} else {
    $LAUNCH_SCRIPT = $env:LAUNCH_SCRIPT
}

$ERROR_REPORTING = $false

mkdir tmp 2>$null

function Start-Venv {
    if ($VENV_DIR -eq '-') {
        Skip-Venv
    }

    if (Test-Path -Path "$VENV_DIR\Scripts\$python") {
        Activate-Venv
    } else {
        $PYTHON_FULLNAME = & $PYTHON -c "import sys; print(sys.executable)"
        Write-Output "Creating venv in directory $VENV_DIR using python $PYTHON_FULLNAME"
        Invoke-Expression "$PYTHON_FULLNAME -m venv $VENV_DIR > tmp/stdout.txt 2> tmp/stderr.txt"
        if ($LASTEXITCODE -eq 0) {
            Activate-Venv
        } else {
            Write-Output "Unable to create venv in directory $VENV_DIR"
        }
    }
}

function Activate-Venv {
    $PYTHON = "$VENV_DIR\Scripts\Python.exe"
    $ACTIVATE = "$VENV_DIR\Scripts\activate.bat"
    Invoke-Expression "cmd.exe /c $ACTIVATE"
    Write-Output "Venv set to $VENV_DIR."
    if ($ACCELERATE -eq 'True') {
        Check-Accelerate
    } else {
        Launch-App
    }
}

function Skip-Venv {
    Write-Output "Venv set to $VENV_DIR."
    if ($ACCELERATE -eq 'True') {
        Check-Accelerate
    } else {
        Launch-App
    }
}

function Check-Accelerate {
    Write-Output 'Checking for accelerate'
    $ACCELERATE = "$VENV_DIR\Scripts\accelerate.exe"
    if (Test-Path -Path $ACCELERATE) {
        Accelerate-Launch
    } else {
        Launch-App
    }
}

function Launch-App {
    Write-Output "Launching with python"
    Invoke-Expression "$PYTHON $LAUNCH_SCRIPT"
    #pause
    exit
}

function Accelerate-Launch {
    Write-Output 'Accelerating'
    Invoke-Expression "$ACCELERATE launch --num_cpu_threads_per_process=6 $LAUNCH_SCRIPT"
    #pause
    exit
}


try {
    if(Get-Command $PYTHON){
        Start-Venv
    }
} Catch {
    Write-Output "Couldn't launch python."
}

webui-user.ps1

[Environment]::SetEnvironmentVariable("PYTHON", "")
[Environment]::SetEnvironmentVariable("GIT", "")
[Environment]::SetEnvironmentVariable("VENV_DIR","")

# Commandline arguments for webui.py, for example: [Environment]::SetEnvironmentVariable("COMMANDLINE_ARGS", "--medvram --opt-split-attention")
[Environment]::SetEnvironmentVariable("COMMANDLINE_ARGS", "")

# script to launch to start the app
# [Environment]::SetEnvironmentVariable("LAUNCH_SCRIPT", "launch.py")

# install command for torch
# [Environment]::SetEnvironmentVariable("TORCH_COMMAND", "pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 --extra-index-url https://download.pytorch.org/whl/cu113")

# Requirements file to use for stable-diffusion-webui
# [Environment]::SetEnvironmentVariable("REQS_FILE", "requirements_versions.txt")

# [Environment]::SetEnvironmentVariable("GFPGAN_PACKAGE", "")
# [Environment]::SetEnvironmentVariable("CLIP_PACKAGE", "")
# [Environment]::SetEnvironmentVariable("OPENCLIP_PACKAGE", "")

# URL to a WHL if you wish to override default xformers windows
# [Environment]::SetEnvironmentVariable("XFORMERS_WINDOWS_PACKAGE", "")

# Uncomment and set to enable an alternate repository URL
# [Environment]::SetEnvironmentVariable("STABLE_DIFFUSION_REPO", "")
# [Environment]::SetEnvironmentVariable("TAMING_TRANSFORMERS_REPO", "")
# [Environment]::SetEnvironmentVariable("K_DIFFUSION_REPO", "")
# [Environment]::SetEnvironmentVariable("CODEFORMER_REPO", "")
# [Environment]::SetEnvironmentVariable("BLIP_REPO", "")

# Uncomment and set to enable a specific revision of a repository
# [Environment]::SetEnvironmentVariable("STABLE_DIFFUSION_COMMIT_HASH", "")
# [Environment]::SetEnvironmentVariable("TAMING_TRANSFORMERS_COMMIT_HASH", "")
# [Environment]::SetEnvironmentVariable("K_DIFFUSION_COMMIT_HASH", "")
# [Environment]::SetEnvironmentVariable("CODEFORMER_COMMIT_HASH", "")
# [Environment]::SetEnvironmentVariable("BLIP_COMMIT_HASH", "")


# Uncomment to enable accelerated launch
# [Environment]::SetEnvironmentVariable("ACCELERATE", "True")

$SCRIPT = "$PSScriptRoot\webui.ps1"
Invoke-Expression "$SCRIPT"

Linux

To install in the default directory /home/$(whoami)/stable-diffusion-webui/, run:

bash <(wget -qO- https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh)

In order to customize the installation, clone the repository into the desired location, change the required variables in webui-user.sh and run :

bash webui.sh

Third party installation guides/scripts:

NixOS: https://github.com/virchau13/automatic1111-webui-nix

Almost Automatic Installation and Launch

To install the required packages via pip without creating a virtual environment, run:

python launch.py

Command line arguments may be passed directly, for example:

python launch.py --opt-split-attention --ckpt ../secret/anime9999.ckpt

Manual Installation

Manual installation is very outdated and probably won't work. check colab in the repo's readme for instructions.

The following process installs everything manually on both Windows or Linux (the latter requiring dir to be replaced by ls):

# install torch with CUDA support. See https://pytorch.org/get-started/locally/ for more instructions if this fails.
pip install torch --extra-index-url https://download.pytorch.org/whl/cu113

# check if torch supports GPU; this must output "True". You need CUDA 11. installed for this. You might be able to use
# a different version, but this is what I tested.
python -c "import torch; print(torch.cuda.is_available())"

# clone web ui and go into its directory
git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
cd stable-diffusion-webui

# clone repositories for Stable Diffusion and (optionally) CodeFormer
mkdir repositories
git clone https://github.com/CompVis/stable-diffusion.git repositories/stable-diffusion
git clone https://github.com/CompVis/taming-transformers.git repositories/taming-transformers
git clone https://github.com/sczhou/CodeFormer.git repositories/CodeFormer
git clone https://github.com/salesforce/BLIP.git repositories/BLIP

# install requirements of Stable Diffusion
pip install transformers==4.19.2 diffusers invisible-watermark --prefer-binary

# install k-diffusion
pip install git+https://github.com/crowsonkb/k-diffusion.git --prefer-binary

# (optional) install GFPGAN (face restoration)
pip install git+https://github.com/TencentARC/GFPGAN.git --prefer-binary

# (optional) install requirements for CodeFormer (face restoration)
pip install -r repositories/CodeFormer/requirements.txt --prefer-binary

# install requirements of web ui
pip install -r requirements.txt  --prefer-binary

# update numpy to latest version
pip install -U numpy  --prefer-binary

# (outside of command line) put stable diffusion model into web ui directory
# the command below must output something like: 1 File(s) 4,265,380,512 bytes
dir model.ckpt

The installation is finished, to start the web ui, run:

python webui.py

Windows 11 WSL2 instructions

To install under a Linux distro in Windows 11's WSL2:

# install conda (if not already done)
wget https://repo.anaconda.com/archive/Anaconda3-2022.05-Linux-x86_64.sh
chmod +x Anaconda3-2022.05-Linux-x86_64.sh
./Anaconda3-2022.05-Linux-x86_64.sh

# Clone webui repo
git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
cd stable-diffusion-webui

# Create and activate conda env
conda env create -f environment-wsl2.yaml
conda activate automatic

At this point, the instructions for the Manual installation may be applied starting at step # clone repositories for Stable Diffusion and (optionally) CodeFormer.

Alternative installation on Windows using Conda

Prerequisites (Only needed if you do not have them). Assumes Chocolatey is installed.
```
# install git
choco install git
# install conda
choco install anaconda3
```
Optional parameters: git, conda

Install (warning: some files exceed multiple gigabytes, make sure you have space first)

Download as .zip and extract or use git to clone.

git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git

Launch the Anaconda prompt. It should be noted that you can use older Python versions, but you may be forced to manually remove features like cache optimization, which will degrade your performance.

# Navigate to the git directory
cd "GIT\StableDiffusion"
# Create environment
conda create -n StableDiffusion python=3.10.6
# Activate environment
conda activate StableDiffusion
# Validate environment is selected
conda env list
# Start local webserver
webui-user.bat
# Wait for "Running on local URL:  http://127.0.0.1:7860" and open that URI.

(Optional) Go to CompVis and download latest model, for example 1.4 and unpack it to ex:
```
GIT\StableDiffusion\models\Stable-diffusion
```
after that restart the server by restarting Anaconda prompt and
```
webui-user.bat
```

Alternative defaults worth trying out:
1. Try euler a (Ancestral Euler) with higher Sampling Steps ex: 40 or others with 100.
2. Set "Settings > User interface > Show image creation progress every N sampling steps" to 1 and pick a deterministic Seed value. Can visually see how image defusion happens and record a .gif with ScreenToGif.
3. Use Restore faces. Generally, better results, but that quality comes at the cost of speed.

This is the Stable Diffusion web UI wiki. Wiki Home

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