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@ -4,6 +4,258 @@ title: Installing Models
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# :octicons-paintbrush-16: Installing Models
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## TO COME
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## Model Weight Files
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The model weight files ('*.ckpt') are the Stable Diffusion "secret
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sauce". They are the product of training the AI on millions of
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captioned images gathered from multiple sources.
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Originally there was only a single Stable Diffusion weights file,
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which many people named `model.ckpt`. Now there are dozens or more
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that have been "fine tuned" to provide particulary styles, genres, or
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other features. InvokeAI allows you to install and run multiple model
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weight files and switch between them quickly in the command-line and
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web interfaces.
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This manual will guide you through installing and configuring model
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weight files.
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## Base Models
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InvokeAI comes with support for a good initial set of models listed in
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the model configuration file `configs/models.yaml`. They are:
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| Model | Weight File | Description | DOWNLOAD FROM |
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| ---------------------- | ----------------------------- |--------------------------------- | ----------------|
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| stable-diffusion-1.5 | v1-5-pruned-emaonly.ckpt | Most recent version of base Stable Diffusion model| https://huggingface.co/runwayml/stable-diffusion-v1-5 |
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| stable-diffusion-1.4 | sd-v1-4.ckpt | Previous version of base Stable Diffusion model | https://huggingface.co/CompVis/stable-diffusion-v-1-4-original |
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| inpainting-1.5 | sd-v1-5-inpainting.ckpt | Stable Diffusion 1.5 model specialized for inpainting | https://huggingface.co/runwayml/stable-diffusion-inpainting |
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| waifu-diffusion-1.3 | model-epoch09-float32.ckpt | Stable Diffusion 1.4 trained to produce anime images | https://huggingface.co/hakurei/waifu-diffusion-v1-3 |
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| <all models> | vae-ft-mse-840000-ema-pruned.ckpt | A fine-tune file add-on file that improves face generation | https://huggingface.co/stabilityai/sd-vae-ft-mse-original/ |
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Note that these files are covered by an "Ethical AI" license which
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forbids certain uses. You will need to create an account on the
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Hugging Face website and accept the license terms before you can
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access the files.
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The predefined configuration file for InvokeAI (located at
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`configs/models.yaml`) provides entries for each of these weights
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files. `stable-diffusion-1.5` is the default model used, and we
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strongly recommend that you install this weights file if nothing else.
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## Community-Contributed Models
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There are too many to list here and more are being contributed every
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day. [This Page](https://rentry.org/sdmodels) hosts an updated list of
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Stable Diffusion models and where they can be obtained.
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## Installation
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There are three ways to install weights files:
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1. During InvokeAI installation, the `preload_models.py` script can
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download them for you.
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2. You can use the command-line interface (CLI) to import, configure
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and modify new models files.
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3. You can download the files manually and add the appropriate entries
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to `models.yaml`.
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### Installation via `preload_models.py`
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This is the most automatic way. Run `scripts/preload_models.py` from
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the console. It will ask you to select which models to download and
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lead you through the steps of setting up a Hugging Face account if you
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haven't done so already.
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To start, from within the InvokeAI directory run the command `python
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scripts/preload_models.py` (Linux/MacOS) or `python
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scripts\preload_models.py` (Windows):
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```
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Loading Python libraries...
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** INTRODUCTION **
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Welcome to InvokeAI. This script will help download the Stable Diffusion weight files
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and other large models that are needed for text to image generation. At any point you may interrupt
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this program and resume later.
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** WEIGHT SELECTION **
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Would you like to download the Stable Diffusion model weights now? [y]
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Choose the weight file(s) you wish to download. Before downloading you
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will be given the option to view and change your selections.
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[1] stable-diffusion-1.5:
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The newest Stable Diffusion version 1.5 weight file (4.27 GB) (recommended)
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Download? [y]
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[2] inpainting-1.5:
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RunwayML SD 1.5 model optimized for inpainting (4.27 GB) (recommended)
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Download? [y]
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[3] stable-diffusion-1.4:
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The original Stable Diffusion version 1.4 weight file (4.27 GB)
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Download? [n] n
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[4] waifu-diffusion-1.3:
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Stable Diffusion 1.4 fine tuned on anime-styled images (4.27)
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Download? [n] y
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[5] ft-mse-improved-autoencoder-840000:
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StabilityAI improved autoencoder fine-tuned for human faces (recommended; 335 MB) (recommended)
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Download? [y] y
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The following weight files will be downloaded:
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[1] stable-diffusion-1.5*
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[2] inpainting-1.5
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[4] waifu-diffusion-1.3
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[5] ft-mse-improved-autoencoder-840000
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*default
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Ok to download? [y]
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** LICENSE AGREEMENT FOR WEIGHT FILES **
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1. To download the Stable Diffusion weight files you need to read and accept the
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CreativeML Responsible AI license. If you have not already done so, please
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create an account using the "Sign Up" button:
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https://huggingface.co
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You will need to verify your email address as part of the HuggingFace
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registration process.
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2. After creating the account, login under your account and accept
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the license terms located here:
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https://huggingface.co/CompVis/stable-diffusion-v-1-4-original
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Press <enter> when you are ready to continue:
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...
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```
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When the script is complete, you will find the downloaded weights
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files in `models/ldm/stable-diffusion-v1` and a matching configuration
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file in `configs/models.yaml`.
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You can run the script again to add any models you didn't select the
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first time. Note that as a safety measure the script will _never_
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remove a previously-installed weights file. You will have to do this
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manually.
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### Installation via the CLI
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You can install a new model, including any of the community-supported
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ones, via the command-line client's `!import_model` command.
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1. First download the desired model weights file and place it under `models/ldm/stable-diffusion-v1/`.
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You may rename the weights file to something more memorable if you wish. Record the path of the
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weights file (e.g. `models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt`)
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2. Launch the `invoke.py` CLI with `python scripts/invoke.py`.
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3. At the `invoke>` command-line, enter the command `!import_model <path to model>`.
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For example:
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`invoke> !import_model models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt`
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(Hint - the CLI supports file path autocompletion. Type a bit of the path
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name and hit <tab> in order to get a choice of possible completions.
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4. Follow the wizard's instructions to complete installation as shown in the example
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here:
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```
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invoke> <b>!import_model models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt</b>
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>> Model import in process. Please enter the values needed to configure this model:
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Name for this model: <b>arabian-nights</b>
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Description of this model: <b>Arabian Nights Fine Tune v1.0</b>
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Configuration file for this model: <b>configs/stable-diffusion/v1-inference.yaml</b>
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Default image width: <b>512</b>
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Default image height: <b>512</b>
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>> New configuration:
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arabian-nights:
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config: configs/stable-diffusion/v1-inference.yaml
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description: Arabian Nights Fine Tune v1.0
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height: 512
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weights: models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt
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width: 512
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OK to import [n]? <b>y</b>
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>> Caching model stable-diffusion-1.4 in system RAM
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>> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt
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| LatentDiffusion: Running in eps-prediction mode
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| DiffusionWrapper has 859.52 M params.
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| Making attention of type 'vanilla' with 512 in_channels
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| Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
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| Making attention of type 'vanilla' with 512 in_channels
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| Using faster float16 precision
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```
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If you've previously installed the fine-tune VAE file `vae-ft-mse-840000-ema-pruned.ckpt`,
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the wizard will also ask you if you want to add this VAE to the model.
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The appropriate entry for this model will be added to `configs/models.yaml` and it will
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be available to use in the CLI immediately.
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The CLI has additional commands for switching among, viewing, editing,
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deleting the available models. These are described in [Command Line
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Client](CLI.md#model-selection-and-importation), but the two most
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frequently-used are `!models` and `!switch <name of model>`. The first
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prints a table of models that InvokeAI knows about and their load
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status. The second will load the requested model and lets you switch
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back and forth quickly among loaded models.
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### Manually editing of `configs/models.yaml`
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If you are comfortable with a text editor then you may simply edit
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`models.yaml` directly.
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First you need to download the desired .ckpt file and place it in
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`models/ldm/stable-diffusion-v1` as descirbed in step #1 in the
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previous section. Record the path to the weights file,
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e.g. `models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt`
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Then using a **text** editor (e.g. the Windows Notepad application),
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open the file `configs/models.yaml`, and add a new stanza that follows
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this model:
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```
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arabian-nights-1.0:
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description: A great fine-tune in Arabian Nights style
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weights: ./models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt
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config: ./configs/stable-diffusion/v1-inference.yaml
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width: 512
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height: 512
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vae: ./models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
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default: false
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```
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* arabian-nights-1.0
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- This is the name of the model that you will refer to from within the
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CLI and the WebGUI when you need to load and use the model.
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* description
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- Any description that you want to add to the model to remind you what
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it is.
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* weights
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- Relative path to the .ckpt weights file for this model.
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* config
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- This is the confusingly-named configuration file for the model itself.
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Use `./configs/stable-diffusion/v1-inference.yaml` unless the model happens
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to need a custom configuration, in which case the place you downloaded it
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from will tell you what to use instead. For example, the runwayML custom
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inpainting model requires the file `configs/stable-diffusion/v1-inpainting-inference.yaml`.
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(This is already inclued in the InvokeAI distribution and configured automatically
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for you by the `preload_models.py` script.
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* vae
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- If you want to add a VAE file to the model, then enter its path here.
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* width, height
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- This is the width and height of the images used to train the model.
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Currently they are always 512 and 512.
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Save the `models.yaml` and relaunch InvokeAI. The new model should be
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available for your use.
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Lincoln Stein