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https://github.com/invoke-ai/InvokeAI.git
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113 lines
3.9 KiB
Markdown
113 lines
3.9 KiB
Markdown
---
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title: Linux
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---
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# :fontawesome-brands-linux: Linux
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## Installation
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1. You will need to install the following prerequisites if they are not already
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available. Use your operating system's preferred installer.
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- Python (version 3.8.5 recommended; higher may work)
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- git
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2. Install the Python Anaconda environment manager.
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```bash
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~$ wget https://repo.anaconda.com/archive/Anaconda3-2022.05-Linux-x86_64.sh
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~$ chmod +x Anaconda3-2022.05-Linux-x86_64.sh
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~$ ./Anaconda3-2022.05-Linux-x86_64.sh
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```
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After installing anaconda, you should log out of your system and log back in. If
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the installation worked, your command prompt will be prefixed by the name of the
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current anaconda environment - `(base)`.
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3. Copy the InvokeAI source code from GitHub:
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```
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(base) ~$ git clone https://github.com/invoke-ai/InvokeAI.git
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```
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This will create InvokeAI folder where you will follow the rest of the steps.
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4. Enter the newly-created InvokeAI folder. From this step forward make sure that you are working in the InvokeAI directory!
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```
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(base) ~$ cd InvokeAI
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(base) ~/InvokeAI$
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```
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5. Use anaconda to copy necessary python packages, create a new python
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environment named `invokeai` and activate the environment.
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```
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(base) ~/InvokeAI$ conda env create
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(base) ~/InvokeAI$ conda activate invokeai
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(invokeai) ~/InvokeAI$
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```
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After these steps, your command prompt will be prefixed by `(invokeai)` as shown
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above.
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6. Load a couple of small machine-learning models required by stable diffusion:
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```
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(invokeai) ~/InvokeAI$ python3 scripts/preload_models.py
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```
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!!! note
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This step is necessary because I modified the original just-in-time
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model loading scheme to allow the script to work on GPU machines that are not
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internet connected. See [Preload Models](../features/OTHER.md#preload-models)
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7. Now you need to install the weights for the stable diffusion model.
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- For running with the released weights, you will first need to set up an acount
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with [Hugging Face](https://huggingface.co).
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- Use your credentials to log in, and then point your browser [here](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original.)
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- You may be asked to sign a license agreement at this point.
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- Click on "Files and versions" near the top of the page, and then click on the
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file named "sd-v1-4.ckpt". You'll be taken to a page that prompts you to click
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the "download" link. Save the file somewhere safe on your local machine.
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Now run the following commands from within the stable-diffusion directory.
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This will create a symbolic link from the stable-diffusion model.ckpt file, to
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the true location of the `sd-v1-4.ckpt` file.
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```
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(invokeai) ~/InvokeAI$ mkdir -p models/ldm/stable-diffusion-v1
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(invokeai) ~/InvokeAI$ ln -sf /path/to/sd-v1-4.ckpt models/ldm/stable-diffusion-v1/model.ckpt
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```
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8. Start generating images!
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```
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# for the pre-release weights use the -l or --liaon400m switch
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(invokeai) ~/InvokeAI$ python3 scripts/invoke.py -l
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# for the post-release weights do not use the switch
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(invokeai) ~/InvokeAI$ python3 scripts/invoke.py
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# for additional configuration switches and arguments, use -h or --help
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(invokeai) ~/InvokeAI$ python3 scripts/invoke.py -h
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```
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9. 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 multiple `ModuleNotFound` errors.
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## Updating to newer versions of the script
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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:
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```
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(invokeai) ~/InvokeAI$ git pull
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```
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This will bring your local copy into sync with the remote one.
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