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* add test-invoke-pip.yml * update requirements-base.txt to fix tests * install requirements-base.txt separate since it requires to have torch already installed also restore origin requirements-base.txt after suc. test in my fork * restore origin requirements add `basicsr>=1.4.2` to requirements-base.txt remove second installation step * re-add previously overseen req in lin-cuda * fix typo in setup.py - `scripts/preload_models.py` * use GFBGAN from branch `basicsr-1.4.2` * remove `basicsr>=1.4.2` from base reqs * add INVOKEAI_ROOT to env * disable upgrade of `pip`, `setuptools` and `wheel` * try to use a venv which should not contain `wheel` * add relative path to pip command * use `configure_invokeai.py --no-interactive --yes` * set grpcio to `<1.51.0` * revert changes to use venv * remove `--prefer-binary` * disable step to create models.yaml since this will not be used anymore with new `configure_invokeai.py` * use `pip install --no-binary=":all:"` * another try to use venv * try uninstalling wheel before installing reqs * dont use requirements.txt as filename * update cache-dependency-path * add facexlib to requirements-base.txt * first install requirements-base.txt * first install `-e .`, then install requirements I know that this is obviously the wrong order, but still have a feeling * add facexlib to requirements.in * remove `-e .` from reqs and install after reqs * unpin torch and torchvision in requirements.in * fix model dl path * fix curl output path * create directory before downloading model * set INVOKEAI_ROOT_PATH https://docs.github.com/en/actions/learn-github-actions/environment-variables#naming-conventions-for-environment-variables * INVOKEAI_ROOT ${{ env.GITHUB_WORKSPACE }}/invokeai * fix matrix stable-diffusion-model-dl-path * fix INVOKEAI_ROOT * fix INVOKEAI_ROOT * add --root and --outdir to run-tests step * create models.yaml from example * fix scripts variable in setup.py by removing unused scripts * fix archive-results path * fix workflow to reflect latest code changes * fix copy paste error * fix job name * fix matrix.stable-diffusion-model * restructure matrix * fix `activate conda env` step * update the environment yamls use same 4 git packages as for pip * rename job in test-invoke-conda * add tqdm to environment-lin-amd.yml * fix python commands in test-invoke-conda.yml Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
28 lines
1.1 KiB
Plaintext
28 lines
1.1 KiB
Plaintext
# This file describes the alternative machine learning models
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# available to InvokeAI script.
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#
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# To add a new model, follow the examples below. Each
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# model requires a model config file, a weights file,
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# and the width and height of the images it
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# was trained on.
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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: models/ldm/stable-diffusion-v1/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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stable-diffusion-1.4:
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description: Stable Diffusion inference model version 1.4
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config: configs/stable-diffusion/v1-inference.yaml
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weights: models/ldm/stable-diffusion-v1/sd-v1-4.ckpt
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vae: models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
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width: 512
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height: 512
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inpainting-1.5:
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weights: models/ldm/stable-diffusion-v1/sd-v1-5-inpainting.ckpt
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config: configs/stable-diffusion/v1-inpainting-inference.yaml
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vae: models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
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description: RunwayML SD 1.5 model optimized for inpainting
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