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Usage
Assuming you setup everything correctly, you can run any UI (interchangeably, but not in parallel) using the command:
docker compose --profile [ui] up --buildwhere [ui] is one of hlky, auto, auto-cpu, or lstein.
The data and output folders are always mounted into the container as /data and /output, use them so if you want to transfer anything from / to the container.
(Optional) If you want to customize the behaviour of the uis, you can create a docker-compose.override.yml and override the CLI_ARGS variable or whatever you want from the main docker-compose.yml file. Example:
services:
auto:
environment:
- CLI_ARGS=--lowvramPossible configuration:
By default: --medvram are given, which allow you to use this model on a 6GB GPU, you can also use --lowvram for lower end GPUs.
You can find the full list of cli arguments here.
This also has support for custom models, put the weights in the folder data/StableDiffusion, you can then change the model from the settings tab.
There is multiple files in data/config/auto such as config.json and ui-config.json which let you which contain additional config for the UI.
put your scripts data/config/auto/scripts and restart the container
First, you have to add --enable-insecure-extension-access to your CLI_ARGS in your docker-compose.override.yml:
services:
auto:
environment:
# put whatever other flags you want
- CLI_ARGS=--enable-insecure-extension-access --allow-code --medvram --xformersThen, put your extensions in data/config/auto/extensions, there is also the option to create a script data/config/auto/startup.sh which will be called on container startup, in case you want to install any additional dependencies for your extensions or anything else.
An example of your startup.sh might looks like this:
# install all packages for the extensions
for s in extensions/*/install.py; do
python "$s"
doneI maintain neither the UI nor the extension, I can't help you.
CPU instance of the above, some stuff might not work, use at your own risk.
By default: --optimized-turbo is given, which allow you to use this model on a 6GB GPU. However, some features might not be available in the mode. You can find the full list of cli arguments here.
This fork might require a preload to work, see #72