InvokeAI/docs/installation/INSTALL_WINDOWS.md

---
title: Windows
---

## **Notebook install (semi-automated)**

We have a
[Jupyter notebook](https://github.com/lstein/stable-diffusion/blob/main/notebooks/Stable-Diffusion-local-Windows.ipynb)
with cell-by-cell installation steps. It will download the code in this repo as
one of the steps, so instead of cloning this repo, simply download the notebook
from the link above and load it up in VSCode (with the appropriate extensions
installed)/Jupyter/JupyterLab and start running the cells one-by-one.

Note that you will need NVIDIA drivers, Python 3.10, and Git installed
beforehand - simplified
[step-by-step instructions](https://github.com/lstein/stable-diffusion/wiki/Easy-peasy-Windows-install)
are available in the wiki (you'll only need steps 1, 2, & 3 ).

## **Manual Install**

### **pip**

See
[Easy-peasy Windows install](https://github.com/lstein/stable-diffusion/wiki/Easy-peasy-Windows-install)
in the wiki

---

### **Conda**

1. Install Anaconda3 (miniconda3 version) from here:
   https://docs.anaconda.com/anaconda/install/windows/

2. Install Git from here: https://git-scm.com/download/win

3. Launch Anaconda from the Windows Start menu. This will bring up a command
   window. Type all the remaining commands in this window.

4. Run the command:

    ```bash
    git clone https://github.com/lstein/stable-diffusion.git
    ```

    This will create stable-diffusion folder where you will follow the rest of
    the steps.

5. Enter the newly-created stable-diffusion folder. From this step forward make
   sure that you are working in the stable-diffusion directory!

    ```bash
    cd stable-diffusion
    ```

6. Run the following two commands:

    ```bash
    conda env create -f environment.yaml    (step 6a)
    conda activate ldm                      (step 6b)
    ```

    This will install all python requirements and activate the "ldm" environment
    which sets PATH and other environment variables properly.

7. Run the command:

    ```bash
    python scripts\preload_models.py
    ```

    This installs several machine learning models that stable diffusion requires.

    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.

8. Now you need to install the weights for the big stable diffusion model.

      - For running with the released weights, you will first need to set up an
        acount with Hugging Face (https://huggingface.co).
      - Use your credentials to log in, and then point your browser at
        https://huggingface.co/CompVis/stable-diffusion-v-1-4-original.
      - 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. Now save the file somewhere safe on your
        local machine.
      - The weight file is >4 GB in size, so downloading may take a while.

      Now run the following commands from **within the stable-diffusion directory**
      to copy the weights file to the right place:

      ```bash
      mkdir -p models\ldm\stable-diffusion-v1
      copy C:\path\to\sd-v1-4.ckpt models\ldm\stable-diffusion-v1\model.ckpt
      ```

    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, you
    may instead create a shortcut to it from within
    `models\ldm\stable-diffusion-v1\`.

9. Start generating images!

    ```bash
    # for the pre-release weights
    python scripts\dream.py -l

    # for the post-release weights
    python scripts\dream.py
    ```

10. Subsequently, to relaunch the script, first activate the Anaconda command
    window (step 3),enter the stable-diffusion directory (step 5,
    `cd \path\to\stable-diffusion`), run `conda activate ldm` (step 6b), and
    then launch the dream script (step 9).

    **Note:** Tildebyte has written an alternative
    ["Easy peasy Windows install"](https://github.com/lstein/stable-diffusion/wiki/Easy-peasy-Windows-install)
    which uses the Windows Powershell and pew. If you are having trouble with
    Anaconda on Windows, give this a try (or try it first!)

---

### Updating to newer versions of the script

This distribution is changing rapidly. If you used the `git clone` method
(step 5) to download the stable-diffusion directory, then to update to the
latest and greatest version, launch the Anaconda window, enter
`stable-diffusion`, and type:

```bash
git pull
conda env update -f environment.yaml
```

This will bring your local copy into sync with the remote one.