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Copy file name to clipboardExpand all lines: README.md
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### Running with Docker
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#### a) Run with Docker Compose
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DISCLAIMER: This currently only works with NVIDIA GPUs
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You need to have [Docker](https://www.docker.com/) installed on your system. Then clone this repository and execute `docker compose up` in the root of the repository. The first time you execute this command will take a long time as all the dependencies are installed. Subsequent runs of the command should start up the webui pretty much instantly. To stop the webui press CTRL+C and wait a few seconds.
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You need to have [Docker](https://www.docker.com/) installed on your system. Then clone this repository and execute `docker compose -f docker/compose.yml up` in the root path of the repository. The first time you execute this command will take a long time as all the dependencies are installed. Subsequent runs of the command should start up the webui pretty much instantly. To stop the webui press CTRL+C and wait a few seconds.
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Models are provided to the Docker container using a bind mount. This means that if you add a new model to the models directory it should be available in the webui after a checkpoint refresh without needing to rebuild or restart the container.
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The server will be accessible at [localhost:7860](localhost:7860)
docker run --gpus all -d -p 7860:7860 -v $(pwd)/models/:/webui/models -v $(pwd)/embeddings:/webui/models $IMG
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# Those `-v` mean mounting your local pre-downloaded model weights, embeddings, extensions( you can also do this for your local textual_inversion_templates, localizations..etc ) to the container, in the same manner.
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```
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#### c) Run on Kubernetes
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Prerequisite:
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- You already have a Kubernetes Cluster in place and kube.conf in your machine.
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- build the docker images as above step (b), and load it to your K8S cluster.
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- Modify the `YOUR-IMAGE-NAME` and `YOUR-LOCAL-PATH` in `docker/k8s-sd-webui.yaml`
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```
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kubectl apply -f docker/k8s-sd-webui.yaml # Create k8s workload and nodeport service
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kubectl get po -l app=stable-diffusion-webui # List the container
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#kubectl wait --for=condition=available endpoints/stable-diffusion-webui-service # wait for pod ready, you can CTRL+C to skip it
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kubectl get svc stable-diffusion-webui-service # To show the access NodePort port and access it thru K8S NodePort
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```
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To debug, you can check logs from `kubectl logs -f deploy/stable-diffusion-webui`
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### Installation on Windows 10/11 with NVidia-GPUs using release package
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1. Download `sd.webui.zip` from [v1.0.0-pre](https://github.com/AUTOMATIC1111/stable-diffusion-webui/releases/tag/v1.0.0-pre) and extract its contents.
Copy file name to clipboardExpand all lines: modules/cmd_args.py
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parser.add_argument("--unix-filenames-sanitization", action='store_true', help="allow any symbols except '/' in filenames. May conflict with your browser and file system")
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parser.add_argument("--filenames-max-length", type=int, default=128, help='maximal length of filenames of saved images. If you override it, it can conflict with your file system')
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parser.add_argument("--no-prompt-history", action='store_true', help="disable read prompt from last generation feature; settings this argument will not create '--data_path/params.txt' file")
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parser.add_argument("--prepare-environment-only", action='store_true', help="launch.py argument: only prepare environment without launching webui run with --skip-torch-cuda-test")
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