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Installation
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You will need to install the following prerequisites if they are not already available. Use your operating system's preferred installer.
- Python (version 3.8.5 recommended; higher may work)
- git
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Install the Python Anaconda environment manager.
~$ wget https://repo.anaconda.com/archive/Anaconda3-2022.05-Linux-x86_64.sh ~$ chmod +x Anaconda3-2022.05-Linux-x86_64.sh ~$ ./Anaconda3-2022.05-Linux-x86_64.sh
After installing anaconda, you should log out of your system and log back in. If the installation worked, your command prompt will be prefixed by the name of the current anaconda environment -
(base)
. -
Copy the InvokeAI source code from GitHub:
(base) ~$ git clone https://github.com/invoke-ai/InvokeAI.git
This will create InvokeAI folder where you will follow the rest of the steps.
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Enter the newly-created InvokeAI folder. From this step forward make sure that you are working in the InvokeAI directory!
(base) ~$ cd InvokeAI (base) ~/InvokeAI$
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Use anaconda to copy necessary python packages, create a new python environment named
invokeai
and activate the environment.(base) ~/InvokeAI$ conda env create (base) ~/InvokeAI$ conda activate invokeai (invokeai) ~/InvokeAI$
After these steps, your command prompt will be prefixed by
(invokeai)
as shown above. -
Load a couple of small machine-learning models required by stable diffusion:
(invokeai) ~/InvokeAI$ python3 scripts/preload_models.py
!!! note
This step is necessary because I modified the original just-in-time model loading scheme to allow the script to work on GPU machines that are not internet connected. See [Preload Models](../features/OTHER.md#preload-models)
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Now you need to install the weights for the stable diffusion model.
- For running with the released weights, you will first need to set up an acount with Hugging Face.
- Use your credentials to log in, and then point your browser here
- You may be asked to sign a license agreement at this point.
- Click on "Files and versions" near the top of the page, and then click on the file named "sd-v1-4.ckpt". You'll be taken to a page that prompts you to click the "download" link. Save the file somewhere safe on your local machine.
Now run the following commands from within the stable-diffusion directory. This will create a symbolic link from the stable-diffusion model.ckpt file, to the true location of the
sd-v1-4.ckpt
file.(invokeai) ~/InvokeAI$ mkdir -p models/ldm/stable-diffusion-v1 (invokeai) ~/InvokeAI$ ln -sf /path/to/sd-v1-4.ckpt models/ldm/stable-diffusion-v1/model.ckpt
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Start generating images!
# for the pre-release weights use the -l or --liaon400m switch (invokeai) ~/InvokeAI$ python3 scripts/invoke.py -l # for the post-release weights do not use the switch (invokeai) ~/InvokeAI$ python3 scripts/invoke.py # for additional configuration switches and arguments, use -h or --help (invokeai) ~/InvokeAI$ python3 scripts/invoke.py -h
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Subsequently, to relaunch the script, be sure to run "conda activate invokeai" (step 5, second command), enter the
InvokeAI
directory, and then launch the invoke script (step 8). If you forget to activate the 'invokeai' environment, the script will fail with multipleModuleNotFound
errors.
Updating to newer versions of the script
This distribution is changing rapidly. If you used the git clone
method (step 5) to download the InvokeAI directory, then to update to the latest and greatest version, launch the Anaconda window, enter InvokeAI
and type:
(invokeai) ~/InvokeAI$ git pull
(invokeai) ~/InvokeAI$ conda env update -f environment.yml
This will bring your local copy into sync with the remote one.