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113 lines
4.3 KiB
Markdown
113 lines
4.3 KiB
Markdown
# **Windows Installation**
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## **Notebook install (semi-automated)**
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We have a [Jupyter
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notebook](https://github.com/lstein/stable-diffusion/blob/main/notebooks/Stable-Diffusion-local-Windows.ipynb)
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with cell-by-cell installation steps. It will download the code in
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this repo as one of the steps, so instead of cloning this repo, simply
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download the notebook from the link above and load it up in VSCode
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(with the appropriate extensions installed)/Jupyter/JupyterLab and
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start running the cells one-by-one.
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Note that you will need NVIDIA drivers, Python 3.10, and Git installed
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beforehand - simplified [step-by-step
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instructions](https://github.com/lstein/stable-diffusion/wiki/Easy-peasy-Windows-install)
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are available in the wiki (you'll only need steps 1, 2, & 3 ).
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## **Manual Install**
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### **pip**
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See [Easy-peasy Windows install](https://github.com/lstein/stable-diffusion/wiki/Easy-peasy-Windows-install)
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in the wiki
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### **Conda**
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1. Install Anaconda3 (miniconda3 version) from here: https://docs.anaconda.com/anaconda/install/windows/
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2. Install Git from here: https://git-scm.com/download/win
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3. Launch Anaconda from the Windows Start menu. This will bring up a command window. Type all the remaining commands in this window.
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4. Run the command:
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```
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git clone https://github.com/invoke-ai/InvokeAI.git
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```
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This will create stable-diffusion folder where you will follow the rest of the steps.
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5. 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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cd InvokeAI
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```
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6. Run the following two commands:
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```
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conda env create -f environment.yaml (step 6a)
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conda activate ldm (step 6b)
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```
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This will install all python requirements and activate the "ldm"
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environment which sets PATH and other environment variables properly.
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7. Run the command:
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```
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python scripts\preload_models.py
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```
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This installs several machine learning models that stable diffusion requires.
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Note: This step is required. This was done because some users may might be blocked by firewalls or have limited internet connectivity for the models to be downloaded just-in-time.
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8. Now you need to install the weights for the big stable diffusion model.
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- For running with the released weights, you will first need to set up an acount with Hugging Face (https://huggingface.co).
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- Use your credentials to log in, and then point your browser at 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 file named `sd-v1-4.ckpt`. You'll be taken to a page that
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prompts you to click the "download" link. Now save the file somewhere safe on your local machine.
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- The weight file is >4 GB in size, so
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downloading may take a while.
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Now run the following commands from **within the InvokeAI directory** to copy the weights file to the right place:
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```
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mkdir -p models\ldm\stable-diffusion-v1
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copy C:\path\to\sd-v1-4.ckpt models\ldm\stable-diffusion-v1\model.ckpt
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```
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Please replace `C:\path\to\sd-v1.4.ckpt` with the correct path to wherever you stashed this file. If you prefer not to copy or move the .ckpt file,
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you may instead create a shortcut to it from within `models\ldm\stable-diffusion-v1\`.
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9. Start generating images!
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```
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# for the pre-release weights
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python scripts\dream.py -l
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# for the post-release weights
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python scripts\dream.py
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```
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10. Subsequently, to relaunch the script, first activate the Anaconda command window (step 3),enter the InvokeAI directory (step 5, `cd \path\to\InvokeAI`), run `conda activate ldm` (step 6b), and then launch the dream script (step 9).
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**Note:** Tildebyte has written an alternative ["Easy peasy Windows
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install"](https://github.com/lstein/stable-diffusion/wiki/Easy-peasy-Windows-install)
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which uses the Windows Powershell and pew. If you are having trouble with Anaconda on Windows, give this a try (or try it first!)
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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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git pull
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conda env update -f environment.yaml
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```
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This will bring your local copy into sync with the remote one.
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