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https://github.com/invoke-ai/InvokeAI
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instead linking modelfile use custom models.yaml
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@ -45,21 +45,16 @@ ARG invokeai_branch=main
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ARG project_name=invokeai
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ARG conda_env_file=environment-lin-cuda.yml
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RUN git clone -b ${invokeai_branch} https://github.com/${invokeai_git}.git "/${project_name}" \
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&& cp \
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"/${project_name}/configs/models.yaml.example" \
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"/${project_name}/configs/models.yaml" \
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&& ln -sf \
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"/${project_name}/environments-and-requirements/${conda_env_file}" \
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"/${project_name}/environment.yml" \
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&& ln -sf \
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/data/models/v1-5-pruned-emaonly.ckpt \
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"/${project_name}/models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt" \
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&& ln -sf \
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/data/outputs/ \
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"/${project_name}/outputs"
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# set workdir
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# set workdir and copy models.yaml
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WORKDIR "/${project_name}"
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COPY docker-build/models.yaml configs/models.yaml
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# install conda env and preload models
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ARG conda_prefix=/opt/conda
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8
docker-build/models.yaml
Normal file
8
docker-build/models.yaml
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@ -0,0 +1,8 @@
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stable-diffusion-1.5:
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description: The newest Stable Diffusion version 1.5 weight file (4.27 GB)
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weights: /data/models/v1-5-pruned-emaonly.ckpt
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config: ./configs/stable-diffusion/v1-inference.yaml
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width: 512
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height: 512
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vae: ./models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
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default: true
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