stable-diffusion-private/cog.yaml at main · asears/stable-diffusion-private · GitHub

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# Configuration for Cog ⚙️
# Reference: https://github.com/replicate/cog/blob/main/docs/yaml.md

build:
  # set to true if your model requires a GPU
  gpu: true

  # a list of ubuntu apt packages to install
  system_packages:
    - "aria2"
    - "ffmpeg"

  # python version in the form '3.8' or '3.8.12'
  python_version: "3.7"

  # a list of packages in the format <package-name>==<version>
  python_packages:
    - "numpy==1.21.6"
    - "torch==1.10.1"
    - "torchvision==0.11.2"
    - "transformers==4.19.2"
    - "open_clip_torch==1.2.1"
    - "autokeras==1.0.19"
    - "torchmetrics==0.6.0"
    - albumentations==0.4.3
    - opencv-python==4.1.2.30
    - pudb==2019.2
    - imageio==2.9.0
    - imageio-ffmpeg==0.4.2
    - pytorch-lightning==1.4.2
    - omegaconf==2.1.1
    - test-tube==0.7.5
    - streamlit==0.73.1
    - einops==0.3.0
    - torch-fidelity==0.3.0
    - transformers==4.19.2
    - torchmetrics==0.6.0
    - kornia==0.6
    - fire==0.4.0
    - jupyterlab==3.3.4

  # commands run after the environment is setup
  run:
    - pip install -e git+https://github.com/CompVis/taming-transformers.git@master#egg=taming-transformers
    - pip install -e git+https://github.com/openai/CLIP.git@main#egg=clip
    - pip install diffusers
    - pip install --upgrade --no-cache-dir gdown
    - curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | bash
    - apt-get install git-lfs
    # - git clone https://huggingface.co/nitrosocke/Nitro-Diffusion /stable-diffusion-checkpoints
    - mkdir /stable-diffusion-checkpoints && cd /stable-diffusion-checkpoints && wget https://pollinations-models.s3.amazonaws.com/v1-5-pruned-emaonly.ckpt
    - git clone https://github.com/CompVis/taming-transformers
    - git clone https://github.com/openai/CLIP
    - git clone https://github.com/deforum/k-diffusion
    - pip install jsonmerge clean-fid resize-right torchdiffeq
    - pip install googletrans==3.1.0a0

# predict.py defines how predictions are run on your model
predict: "predict.py:Predictor"