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