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Installing Models#

Checkpoint and Diffusers Models#

The model checkpoint 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. In addition, there are several new formats that improve on the original checkpoint format: a .safetensors format which prevents malware from masquerading as a model, and diffusers models, the most recent innovation.

InvokeAI supports all three formats but strongly prefers the diffusers format. These are distributed as directories containing multiple subfolders, each of which contains a different aspect of the model. The advantage of this is that the models load from disk really fast. Another advantage is that diffusers models are supported by a large and active set of open source developers working at and with HuggingFace organization, and improvements in both rendering quality and performance are being made at a rapid pace. Among other features is the ability to download and install a diffusers model just by providing its HuggingFace repository ID.

While InvokeAI will continue to support .ckpt and .safetensors models for the near future, these are deprecated and support will likely be withdrawn at some point in the not-too-distant future.

This manual will guide you through installing and configuring model weight files and converting legacy .ckpt and .safetensors files into performant diffusers models.

Base Models#

InvokeAI comes with support for a good set of starter models. You'll find them listed in the master models file configs/INITIAL_MODELS.yaml in the InvokeAI root directory. The subset that are currently installed are found in configs/models.yaml. As of v2.3.1, the list of starter models is:

Model Name HuggingFace Repo ID Description URL
stable-diffusion-1.5 runwayml/stable-diffusion-v1-5 Stable Diffusion version 1.5 diffusers model (4.27 GB)
sd-inpainting-1.5 runwayml/stable-diffusion-inpainting RunwayML SD 1.5 model optimized for inpainting, diffusers version (4.27 GB)
stable-diffusion-2.1 stabilityai/stable-diffusion-2-1 Stable Diffusion version 2.1 diffusers model, trained on 768 pixel images (5.21 GB)
sd-inpainting-2.0 stabilityai/stable-diffusion-2-inpainting Stable Diffusion version 2.0 inpainting model (5.21 GB)
analog-diffusion-1.0 wavymulder/Analog-Diffusion An SD-1.5 model trained on diverse analog photographs (2.13 GB)
deliberate-1.0 XpucT/Deliberate Versatile model that produces detailed images up to 768px (4.27 GB)
d&d-diffusion-1.0 0xJustin/Dungeons-and-Diffusion Dungeons & Dragons characters (2.13 GB)
dreamlike-photoreal-2.0 dreamlike-art/dreamlike-photoreal-2.0 A photorealistic model trained on 768 pixel images based on SD 1.5 (2.13 GB)
inkpunk-1.0 Envvi/Inkpunk-Diffusion Stylized illustrations inspired by Gorillaz, FLCL and Shinkawa; prompt with "nvinkpunk" (4.27 GB)
openjourney-4.0 prompthero/openjourney An SD 1.5 model fine tuned on Midjourney; prompt with "mdjrny-v4 style" (2.13 GB)
portrait-plus-1.0 wavymulder/portraitplus An SD-1.5 model trained on close range portraits of people; prompt with "portrait+" (2.13 GB)
seek-art-mega-1.0 coreco/seek.art_MEGA A general use SD-1.5 "anything" model that supports multiple styles (2.1 GB)
trinart-2.0 naclbit/trinart_stable_diffusion_v2 An SD-1.5 model finetuned with ~40K assorted high resolution manga/anime-style images (2.13 GB)
waifu-diffusion-1.4 hakurei/waifu-diffusion An SD-1.5 model trained on 680k anime/manga-style images (2.13 GB)

Note that these files are covered by an "Ethical AI" license which forbids certain uses. When you initially download them, you are asked to accept the license terms. In addition, some of these models carry additional license terms that limit their use in commercial applications or on public servers. Be sure to familiarize yourself with the model terms by visiting the URLs in the table above.

Community-Contributed Models#

There are too many to list here and more are being contributed every day. HuggingFace is a great resource for diffusers models, and is also the home of a fast-growing repository of embedding (".bin") models that add subjects and/or styles to your images. The latter are automatically installed on the fly when you include the text <concept-name> in your prompt. See Concepts Library for more information.

Another popular site for community-contributed models is CIVITAI. This extensive site currently supports only .safetensors and .ckpt models, but they can be easily loaded into InvokeAI and/or converted into optimized diffusers models. Be aware that CIVITAI hosts many models that generate NSFW content.


InvokeAI 2.3.x does not support directly importing and running Stable Diffusion version 2 checkpoint models. You may instead convert them into diffusers models using the conversion methods described below.


There are multiple ways to install and manage models:

  1. The invokeai-configure script which will download and install them for you.

  2. The command-line tool (CLI) has commands that allows you to import, configure and modify models files.

  3. The web interface (WebUI) has a GUI for importing and managing models.

Installation via invokeai-configure#

From the invoke launcher, choose option (6) "re-run the configure script to download new models." This will launch the same script that prompted you to select models at install time. You can use this to add models that you skipped the first time around. It is all right to specify a model that was previously downloaded; the script will just confirm that the files are complete.

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.

Installing individual .ckpt and .safetensors models#

If the model is already downloaded to your local disk, use !import_model /path/to/file.ckpt to load it. For example:

invoke> !import_model C:/Users/fred/Downloads/martians.safetensors

Forward Slashes

On Windows systems, use forward slashes rather than backslashes in your file paths. If you do use backslashes, you must double them like this: C:\\Users\\fred\\Downloads\\martians.safetensors

Alternatively you can directly import the file using its URL:

invoke> !import_model

For this to work, the URL must not be password-protected. Otherwise you will receive a 404 error.

When you import a legacy model, the CLI will first ask you what type of model this is. You can indicate whether it is a model based on Stable Diffusion 1.x (1.4 or 1.5), one based on Stable Diffusion 2.x, or a 1.x inpainting model. Be careful to indicate the correct model type, or it will not load correctly. You can correct the model type after the fact using the !edit_model command.

The system will then ask you a few other questions about the model, including what size image it was trained on (usually 512x512), what name and description you wish to use for it, and whether you would like to install a custom VAE (variable autoencoder) file for the model. For recent models, the answer to the VAE question is usually "no," but it won't hurt to answer "yes".

After importing, the model will load. If this is successful, you will be asked if you want to keep the model loaded in memory to start generating immediately. You'll also be asked if you wish to make this the default model on startup. You can change this later using !edit_model.

Importing a batch of .ckpt and .safetensors models from a directory#

You may also point !import_model to a directory containing a set of .ckpt or .safetensors files. They will be imported en masse.


invoke> !import_model C:/Users/fred/Downloads/civitai_models/

You will be given the option to import all models found in the directory, or select which ones to import. If there are subfolders within the directory, they will be searched for models to import.

Installing diffusers models#

You can install a diffusers model from the HuggingFace site using !import_model and the HuggingFace repo_id for the model:

invoke> !import_model andite/anything-v4.0

Alternatively, you can download the model to disk and import it from there. The model may be distributed as a ZIP file, or as a Git repository:

invoke> !import_model C:/Users/fred/Downloads/andite--anything-v4.0

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.

On Windows, you can drag model files onto the command-line

Once you have typed in !import_model, you can drag the model file or directory onto the command-line to insert the model path. This way, you don't need to type it or copy/paste. However, you will need to reverse or double backslashes as noted above.

Before installing, the CLI will ask you for a short name and description for the model, whether to make this the default model that is loaded at InvokeAI startup time, and whether to replace its VAE. Generally the answer to the latter question is "no".

Converting legacy models into diffusers#

The CLI !convert_model will convert a .safetensors or .ckpt models file into diffusers and install it.This will enable the model to load and run faster without loss of image quality.

The usage is identical to !import_model. You may point the command to either a downloaded model file on disk, or to a (non-password protected) URL:

invoke> !convert_model C:/Users/fred/Downloads/martians.safetensors

After a successful conversion, the CLI will offer you the option of deleting the original .ckpt or .safetensors file.

Optimizing a previously-installed model#

Lastly, if you have previously installed a .ckpt or .safetensors file and wish to convert it into a diffusers model, you can do this without re-downloading and converting the original file using the !optimize_model command. Simply pass the short name of an existing installed model:

invoke> !optimize_model martians-v1.0

The model will be converted into diffusers format and replace the previously installed version. You will again be offered the opportunity to delete the original .ckpt or .safetensors file.

There are a whole series of additional model management commands in the CLI that you can read about in Command-Line Interface. These include:

  • !models - List all installed models
  • !switch <model name> - Switch to the indicated model
  • !edit_model <model name> - Edit the indicated model to change its name, description or other properties
  • !del_model <model name> - Delete the indicated model

Manually editing configs/models.yaml#

If you are comfortable with a text editor then you may simply edit models.yaml directly.

You will need to download the desired .ckpt/.safetensors file and place it somewhere on your machine's filesystem. Alternatively, for a diffusers model, record the repo_id or download the whole model directory. 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:

A legacy model#

A legacy .ckpt or .safetensors entry will look like this:

  description: A great fine-tune in Arabian Nights style
  weights: ./path/to/arabian-nights-1.0.ckpt
  config: ./configs/stable-diffusion/v1-inference.yaml
  format: ckpt
  width: 512
  height: 512
  default: false

Note that format is ckpt for both .ckpt and .safetensors files.

A diffusers model#

A stanza for a diffusers model will look like this for a HuggingFace model with a repository ID:

  description: An even better fine-tune of the Arabian Nights
  repo_id: captahab/arabian-nights-1.1
  format: diffusers
  default: true

And for a downloaded directory:

  description: An even better fine-tune of the Arabian Nights
  path: /path/to/captahab-arabian-nights-1.1
  format: diffusers
  default: true

There is additional syntax for indicating an external VAE to use with this model. See INITIAL_MODELS.yaml and models.yaml for examples.

After you save the modified models.yaml file relaunch invokeai. The new model will now be available for your use.

Installation via the WebUI#

To access the WebUI Model Manager, click on the button that looks like a cube in the upper right side of the browser screen. This will bring up a dialogue that lists the models you have already installed, and allows you to load, delete or edit them:


To add a new model, click on + Add New and select to either a checkpoint/safetensors model, or a diffusers model:


In this example, we chose Add Diffusers. As shown in the figure below, a new dialogue prompts you to enter the name to use for the model, its description, and either the location of the diffusers model on disk, or its Repo ID on the HuggingFace web site. If you choose to enter a path to disk, the system will autocomplete for you as you type:


Press Add Model at the bottom of the dialogue (scrolled out of site in the figure), and the model will be downloaded, imported, and registered in models.yaml.

The Add Checkpoint/Safetensor Model option is similar, except that in this case you can choose to scan an entire folder for checkpoint/safetensors files to import. Simply type in the path of the directory and press the "Search" icon. This will display the .ckpt and .safetensors found inside the directory and its subfolders, and allow you to choose which ones to import:


Model Management Startup Options#

The invoke launcher and the invokeai script accept a series of command-line arguments that modify InvokeAI's behavior when loading models. These can be provided on the command line, or added to the InvokeAI root directory's invokeai.init initialization file.

The arguments are:

  • --model <model name> -- Start up with the indicated model loaded
  • --ckpt_convert -- When a checkpoint/safetensors model is loaded, convert it into a diffusers model in memory. This does not permanently save the converted model to disk.
  • --autoconvert <path/to/directory> -- Scan the indicated directory path for new checkpoint/safetensors files, convert them into diffusers models, and import them into InvokeAI.

Here is an example of providing an argument on the command line using the launch script: --autoconvert /home/fred/stable-diffusion-checkpoints

And here is what the same argument looks like in invokeai.init:

--autoconvert /home/fred/stable-diffusion-checkpoints

Last update: April 8, 2023
Created: October 29, 2022