Installing Stable Diffusion AI image generator

Install the Git client

Install Miniconda 3

Clone the Stable Diffusion GitHub repository

  • Cerate another directory on the same level: stable-diffusioncd

Download the latest Stable Diffusion checkpoint

Configure the Python environment with Miniconda

  • Start Miniconda from the Start Menu
  • In the Miniconda terminal execute the following lines
    • Create the ldm Python environment
      conda env create -f environment.yaml
      • this will cerate the Conda environment files at C:\Users\MY_USER_NAME\.conda\envs
        If anything goes wrong during the environment creation, delete the ldm folder and run this command again.
    • Activate the just created environment
      conda activate ldm

Copy the checkpoint file into the models directory

  • Open a terminal in the stable-diffusion directory
  • Create a directory for the model
    mkdir models\ldm\stable-diffusion-v1
  • Step into the new directory
    cd models\ldm\stable-diffusion-v1
  • Copy the downloaded .ckpt file into the models\ldm\stable-diffusion-v1 directory and rename it to model.ckpt
    copy C:\Users\MY_USER_NAME\Downloads\sd-v1-4-full-ema.ckpt model.ckpt

To use Stable Diffusion

Activate the Python environment

  • Start Miniconda 3 from the start menu
  • In the terminal navigate to the stable-diffusion directory
  • Activate the ldm Anaconda environment
    conda activate ldm

Generate the image

We will call a Python script with the –prompt argument and type the English description of the image

python scripts/ --prompt "a close-up portrait of a cat by pablo picasso, vivid, abstract art, colorful, vibrant" --plms --n_iter 5 --n_samples 1

The image will be created in the stable-diffusion\outputs\txt2img-samples\samples directory


To get help on using Stable Diffusion execute
python scripts/ --help

  • –plms specifies how images are sampled
  • –n_iter 5 sets the number of iterations
  • –n_samples 1 – the nmber of samples generated

For more information see

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