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InvokeAI Version 3.0.1

InvokeAI Version 3.0.1

InvokeAI is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies. InvokeAI offers an industry leading Web Interface, interactive Command Line Interface, and also serves as the foundation for multiple commercial products.

InvokeAI version 3.0.1 adds support for rendering with Stable Diffusion XL Version 1.0 directly in the Text2Image and Image2Image panels, as well as many internal changes.

To learn more about InvokeAI, please see our Documentation Pages.

What’s New in v3.0.1

  • Stable Diffusion XL support in the Text2Image and Image2Image (but not the Unified Canvas).
  • Can install and run both diffusers-style and .safetensors-style SDXL models.
  • Download Stable Diffusion XL 1.0 (base and refiner) using the model installer or the Web UI-based Model Manager
  • Invisible watermarking, which is recommended for use with Stable Diffusion XL, is now available as an option in the Web UI settings dialogue.
  • The NSFW detector, which was missing in 3.0.0, is again available. It can be activated as an option in the settings dialogue.
  • During initial installation, a set of recommended ControlNet, LoRA and Textual Inversion embedding files will now be downloaded and installed by default, along with several “starter” main models.
  • User interface cleanup to reduce visual clutter and increase usability.

Recent Changes

Since RC3, the following has changed:

  • Fixed crash on Macintosh M1 machines when rendering SDXL images
  • Fixed black images when generating on Macintoshes using the Unipc scheduler (falls back to CPU; slow)

Since RC2, the following has changed:

  • Added compatibility with Python 3.11
  • Updated diffusers to 0.19.0
  • Cleaned up console logging - can now change logging level as described in the docs
  • Added download of an updated SDXL VAE “sdxl-vae-fix” that may correct certain image artifacts in SDXL-1.0 models
  • Prevent web crashes during certain resize operations

Developer changes:

  • Reformatted the whole code base with the “black” tool for a consistent coding style
  • Add pre-commit hooks to reformat committed code on the fly

Installation / Upgrading

Installing using the InvokeAI zip file installer

To install 3.0.1 please download the zip file at the bottom of the release notes (under “Assets”), unpack it, and then double-click to launch the script install.sh (Macintosh, Linux) or install.bat (Windows). Alternatively, you can open a command-line window and execute the installation script directly.

If you have an earlier version of InvokeAI installed, we strongly recommend that you install into a new directory, such as invokeai-3 instead of the previously-used invokeai directory. We provide a script that will let you migrate your old models and settings into the new directory, described below.

InvokeAI-installer-v3.0.1.zip

Upgrading in place

All users can upgrade from 3.0.0 using the launcher’s “upgrade” facility. If you are on a Linux or Macintosh, you may also upgrade a 2.3.2 or higher version of InvokeAI to 3.0 using this recipe, but upgrading from 2.3 will not work on Windows due to a 2.3.5 bug (see workaround below):

  1. Enter the root directory you wish to upgrade
  2. Launch invoke.sh or invoke.bat
  3. Select the upgrade menu option [9]
  4. Select “Manually enter the tag name for the version you wish to update to” option [3]
  5. Select option [1] to upgrade to the latest version.
  6. When the upgrade is complete, the main menu will reappear. Choose “rerun the configure script to fix a broken install” option [7]

Windows users can instead follow this recipe:

  1. Enter the 2.3 root directory you wish to upgrade
  2. Launch invoke.sh or invoke.bat
  3. Select the “Developer’s console” option [8]
  4. Type the following commands:
pip install "invokeai @ https://github.com/invoke-ai/InvokeAI/archive/refs/tags/v3.0.1.zip" --use-pep517 --upgrade
invokeai-configure --root .

This will produce a working 3.0 directory. You may now launch the WebUI in the usual way, by selecting option [1] from the launcher script

After you have confirmed everything is working, you may remove the following backup directories and files:

  • invokeai.init.orig
  • models.orig
  • configs/models.yaml.orig
  • embeddings
  • loras

To get back to a working 2.3 directory, rename all the ‘*.orig” files and directories to their original names (without the .orig), run the update script again, and select [1] “Update to the latest official release”.

What to do if problems occur during the install

Due to the large number of Python libraries that InvokeAI requires, as well as the large size of the newer SDXL models, you may experience glitches during the install process. This particularly affects Windows users. Please see the Installation Troubleshooting Guide for solutions.

Migrating models and settings from a 2.3 InvokeAI root directory to a 3.0 directory

We provide a script, invokeai-migrate3, which will copy your models and settings from a 2.3-format root directory to a new 3.0 directory. To run it, execute the launcher and select option [8] “Developer’s console”. This will take you to a new command line interface. On the command line, type:

invokeai-migrate3 --from <path to 2.3 directory> --to <path to 3.0 directory>

Provide the old and new directory names with the --from and --to arguments respectively. This will migrate your models as well as the settings inside invokeai.init. You may provide the same --from and --to directories in order ot upgrade a 2.3 root directory in place. (The original models and configuration files will be backed up.)

Upgrading using pip

Developers and power users can upgrade to the current version by activating the InvokeAI environment and then using:

pip install --use-pep517 --upgrade InvokeAI
invokeai-configure --skip-sd-weights

You may specify a particular version by adding the version number to the command, as in:

pip install --use-pep517 --upgrade  InvokeAI==3.0.1
invokeai-configure --skip-sd-weights

Important: After doing the pip install, it is necessary to invokeai-configure in order to download new core models needed to load and convert Stable Diffusion XL .safetensors files. The web server will refuse to start if you do not do so.

Getting Started with SDXL

Stable Diffusion XL (SDXL) is the latest generation of StabilityAI’s image generation models, capable of producing high quality 1024x1024 photorealistic images as well as many other visual styles. SDXL comes with two models, a “base” model that generates the initial image, and a “refiner” model that takes the initial image and improves on it in an img2img manner. In many cases, just the base model will give satisfactory results.

To download the base and refiner SDXL models, you have several options:

  1. Select option [5] from the invoke.bat launcher script, and select the base model, and optionally the refiner, from the checkbox list of “starter” models.
  2. Use the Web’s Model Manager to select “Import Models” and when prompted provide the HuggingFace repo_ids for the two models:
    • stabilityai/stable-diffusion-xl-base-1.0
    • stabilityai/stable-diffusion-xl-refiner-1.0 (note that these are preliminary IDs - these notes are being written before the SDXL release)
  3. Download the models manually and cut and paste their paths into the Location field in “Import Models”

Also be aware that SDXL requires at 6-8 GB of VRAM in order to render 1024x1024 images and a minimum of 16 GB of RAM. For best performance, we recommend the following settings in invokeai.yaml:

precision: float16
max_cache_size: 12.0
max_vram_cache_size: 0.0

Users with 12 GB or more VRAM can reduce the time waiting for the image to start generating by setting max_vram_cache_size to 6 GB or higher.

Known Bugs in 3.0

This is a list of known bugs in 3.0.1 as well as features that are planned for inclusion in later releases:

  • Variant generation was not fully functional and did not make it into the release. It will be added in the next point release.
  • Perlin noise and symmetrical tiling were not widely used and have been removed from the feature set.
  • Face restoration is no longer needed due to the improvent in recent SD 1.x, 2.x and XL models and has been removed from the feature set.
  • High res optimization has been removed from the basic user interface as we experiment with better ways to achieve good results with nodes. However, you will find several community-contributed high-res optimization pipelines in the Community Nodes Discord channel at https://discord.com/channels/1020123559063990373/1130291608097661000 for use with the experimental Node Editor.
  • There is no easy way to import a directory of version 2.3 generated images into the 3.0 gallery while preserving metadata. We hope to provide an import script in the not so distant future.

Getting Help

For support, please use this repository’s GitHub Issues tracking service, or join our Discord.

Contributing

As a community-supported project, we rely on volunteers and enthusiasts for continued innovation and polish. Everything from minor documentation fixes to major feature additions are welcome. To get started as a contributor, please see How to Contribute.

What’s Changed

New Contributors

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v3.0.0…v3.0.1

Source code and previous installer files

The files below include the InvokeAI installer zip file, the full source code, and previous release candidates for 3.0.1

InvokeAI 3.0.0

InvokeAI Version 3.0.0

InvokeAI is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies. InvokeAI offers an industry leading Web Interface, interactive Command Line Interface, and also serves as the foundation for multiple commercial products.

InvokeAI version 3.0.0 represents a major advance in functionality and ease compared with the last official release, 2.3.5.

Please use the 3.0.0 release discussion thread, for comments on this version, including feature requests, enhancement suggestions and other non-critical issues. Report bugs to InvokeAI Issues. For interactive support with the development team, contributors and user community, you are invited join the InvokeAI Discord Server.

To learn more about InvokeAI, please see our Documentation Pages.

What’s New in v3.0.0

Quite a lot has changed, both internally and externally.

Web User Interface:

  • A ControlNet interface that gives you fine control over such things as the posture of figures in generated images by providing an image that illustrates the end result you wish to achieve.
  • A Dynamic Prompts interface that lets you generate combinations of prompt elements.
  • Preliminary support for Stable Diffusion XL the latest iteration of Stability AI’s image generation models.
  • A redesigned user interface which makes it easier to access frequently-used elements, such as the random seed generator.
  • The ability to create multiple image galleries, allowing you to organize your generated images topically or chronologically.
  • An experimental Nodes Editor that lets you design and execute complex image generation operations using a point-and-click interface. To activate this, please use the settings icon at the upper right of the Web UI.
  • Macintosh users can now load models at half-precision (float16) in order to reduce the amount of RAM.
  • Advanced users can choose earlier CLIP layers during generation to produce a larger variety of images.
  • Long prompt support (>77 tokens).
  • Memory and speed improvements.

The WebUI can now be launched from the command line using either invokeai-web (preferred new way) or invokeai --web (deprecated old way).

Command Line Tool

The previous command line tool has been removed and replaced with a new developer-oriented tool invokeai-node-cli that allows you to experiment with InvokeAI nodes.

Installer

The console-based model installer, invokeai-model-install has been redesigned and now provides tabs for installing checkpoint models, diffusers models, ControlNet models, LoRAs, and Textual Inversion embeddings. You can install models stored locally on disk, or install them using their web URLs or Repo_IDs.

Internal

Internally the code base has been completely rewritten to be much easier to maintain and extend. Importantly, all image generation options are now represented as “nodes”, which are small pieces of code that transform inputs into outputs and can be connected together into a graph of operations. Generation and image manipulation operations can now be easily extended by writing a new InvokeAI nodes.

Installation / Upgrading

Installing using the InvokeAI zip file installer

To install 3.0.0 please download the zip file at the bottom of the release notes (under “Assets”), unpack it, and then double-click to launch the script install.sh (Macintosh, Linux) or install.bat (Windows). Alternatively, you can open a command-line window and execute the installation script directly.

If you have an earlier version of InvokeAI installed, we strongly recommend that you install into a new directory, such as invokeai-3 instead of the previously-used invokeai directory. We provide a script that will let you migrate your old models and settings into the new directory, described below.

InvokeAI-installer-v3.0.0.zip

Upgrading in place

All users can upgrade from the 3.0 beta releases using the launcher’s “upgrade” facility. If you are on a Linux or Macintosh, you may also upgrade a 2.3.2 or higher version of InvokeAI to 3.0 using this recipe, but upgrading from 2.3 will not work on Windows due to a 2.3.5 bug (see workaround below):

  1. Enter the 2.3 root directory you wish to upgrade
  2. Launch invoke.sh or invoke.bat
  3. Select the upgrade menu option [9]
  4. Select “Manually enter the tag name for the version you wish to update to” option [3]
  5. Select option [1] to upgrade to the latest version.
  6. When the upgrade is complete, the main menu will reappear. Choose “rerun the configure script to fix a broken install” option [7]

Windows users can instead follow this recipe:

  1. Enter the 2.3 root directory you wish to upgrade
  2. Launch invoke.sh or invoke.bat
  3. Select the “Developer’s console” option [8]
  4. Type the following command:
pip install "invokeai @ https://github.com/invoke-ai/InvokeAI/archive/refs/tags/v3.0.0.zip" --use-pep517 --upgrade

This will produce a working 3.0 directory. You may now launch the WebUI in the usual way, by selecting option [1] from the launcher script

After you have confirmed everything is working, you may remove the following backup directories and files:

  • invokeai.init.orig
  • models.orig
  • configs/models.yaml.orig
  • embeddings
  • loras

To get back to a working 2.3 directory, rename all the ‘*.orig” files and directories to their original names (without the .orig), run the update script again, and select [1] “Update to the latest official release”.

Migrating models and settings from a 2.3 InvokeAI root directory to a 3.0 directory

We provide a script, invokeai-migrate3, which will copy your models and settings from a 2.3-format root directory to a new 3.0 directory. To run it, execute the launcher and select option [8] “Developer’s console”. This will take you to a new command line interface. On the command line, type:

invokeai-migrate3 --from <path to 2.3 directory> --to <path to 3.0 directory>

Provide the old and new directory names with the --from and --to arguments respectively. This will migrate your models as well as the settings inside invokeai.init. You may provide the same --from and --to directories in order ot upgrade a 2.3 root directory in place. (The original models and configuration files will be backed up.)

Upgrading using pip

Once 3.0.0 is released, developers and power users can upgrade to the current version by activating the InvokeAI environment and then using:

pip install --use-pep517 --upgrade InvokeAI

You may specify a particular version by adding the version number to the command, as in:

pip install --use-pep517 --upgrade  InvokeAI==3.0.0

To upgrade to an xformers version if you are not currently using xformers, use:

pip install --use-pep517 --upgrade InvokeAI[xformers]

You can see which versions are available by going to The PyPI InvokeAI Project Page

Getting Started with SDXL

Stable Diffusion XL (SDXL) is the latest generation of StabilityAI’s image generation models, capable of producing high quality 1024x1024 photorealistic images as well as many other visual styles. As of the current time (July 2023) SDXL had not been officially released, but a pre-release 0.9 version is widely available. InvokeAI provides support for SDXL image generation via its Nodes Editor, a user interface that allows you to create and customize complex image generation pipelines using a drag-and-drop interface. Currently SDXL generation is not directly supported in the text2image, image2image, and canvas panels, but we expect to add this feature as soon as SDXL 1.0 is officially released.

SDXL comes with two models, a “base” model that generates the initial image, and a “refiner” model that takes the initial image and improves on it in an img2img manner. For best results, the initial image is handed off from the base to the refiner before all the denoising steps are complete. It is not clear whether SDXL 1.0, when it is released, will require the refiner.

To experiment with SDXL, you’ll need the “base” and “refiner” models. Currently a beta version of SDXL, version 0.9, is available from HuggingFace for research purposes. To obtain access, you will need to register with HF at https://huggingface.co/join, obtain an access token at https://huggingface.co/settings/tokens, and add the access token to your environment. To do this, run the InvokeAI launcher script, activate the InvokeAI virtual environment with option [8], and type the command huggingface-cli login. Paste in your access token from HuggingFace and hit return (the token will not be echoed to the screen). Alternatively, select launcher option [6] “Change InvokeAI startup options” and paste the HF token into the indicated field.

Now navigate to https://huggingface.co/stabilityai/stable-diffusion-xl-base-0.9 and fill out the access request form for research use. You will be granted instant access to download. Next launch the InvokeAI console-based model installer by selecting launcher option [5] or by activating the virtual environment and giving the command invokeai-model-install. In the STARTER MODELS section, select the checkboxes for stable-diffusion-xl-base-0-9 and stable-diffusion-xl-refiner-0-9. Press Apply Changes to install the models and keep the installer running, or Apply Changes and Exit to install the models and exit back to the launcher menu.

Alternatively you can install these models from the Web UI Model Manager (cube at the bottom of the left-hand panel) and navigate to Import Models. In the field labeled Location type in the repo id of the base model, which is stabilityai/stable-diffusion-xl-base-0.9. Press Add Model and wait for the model to download and install. After receiving confirmation that the model installed, repeat with stabilityai/stable-diffusion-xl-refiner-0.9.

Note that these are large models (12 GB each) so be prepared to wait a while.

To use the installed models you will need to activate the Node Editor, an advanced feature of InvokeAI. Go to the Settings (gear) icon on the upper right of the Web interface, and activate “Enable Nodes Editor”. After reloading the page, an inverted “Y” will appear on the left-hand panel. This is the Node Editor.

Enter the Node Editor and click the Upload button to upload either the SDXL base-only or SDXL base+refiner pipelines (right click to save these .json files to disk). This will load and display a flow diagram showing the (many complex) steps in generating an SDXL image.

Ensure that the SDXL Model Loader (leftmost column, bottom) is set to load the SDXL base model on your system, and that the SDXL Refiner Model Loader (third column, top) is set to load the SDXL refiner model on your system. Find the nodes that contain the example prompt and style (“bluebird in a sakura tree” and “chinese classical painting”) and replace them with the prompt and style of your choice. Then press the Invoke button. If all goes well, an image will eventually be generated and added to the image gallery. Unlike standard rendering, intermediate images are not (yet) displayed during rendering.

Be aware that SDXL support is an experimental feature and is not 100% stable. When designing your own SDXL pipelines, be aware that there are certain settings that will have a disproportionate effect on image quality. In particular, the latents decode VAE step must be run at fp32 precision (using a slider at the bottom of the VAE node), and that images will change dramatically as the denoising threshold used by the refiner is adjusted.

Also be aware that SDXL requires at 6-8 GB of VRAM in order to render 1024x1024 images and a minimum of 16 GB of RAM. For best performance, we recommend the following settings in invokeai.yaml:

precision: float16
max_cache_size: 12.0
max_vram_cache_size: 0.0

Known Bugs in 3.0

This is a list of known bugs in 3.0 as well as features that are planned for inclusion in later releases:

  • On Macintoshes with MPS, Stable Diffusion 2 models will not render properly. This will be corrected in the next point release.
  • Variant generation was not fully functional and did not make it into the release. It will be added in the next point release.
  • Perlin noise and symmetrical tiling were not widely used and have been removed from the feature set.
  • Face restoration is no longer needed due to the improvent in recent SD 1.x, 2.x and XL models and has been removed from the feature set.
  • High res optimization has been removed from the basic user interface as we experiment with better ways to achieve good results with nodes. However, you will find several community-contributed high-res optimization pipelines in the Community Nodes Discord channel at https://discord.com/channels/1020123559063990373/1130291608097661000 for use with the experimental Node Editor.
  • There is no easy way to import a directory of version 2.3 generated images into the 3.0 gallery while preserving metadata. We hope to provide an import script in the not so distant future.
  • The NSFW checker (blurs explicit images) is currently disabled but will be reenabled in time for the next release.

Getting Help

For support, please use this repository’s GitHub Issues tracking service, or join our Discord.

Contributing

As a community-supported project, we rely on volunteers and enthusiasts for continued innovation and polish. Everything from minor documentation fixes to major feature additions are welcome. To get started as a contributor, please see How to Contribute.

What’s Changed Since 2.3.5

New Contributors

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v2.3.5…v3.0.0rc2

InvokeAI 2.3.5.post2

We are pleased to announce a minor update to InvokeAI with the release of version 2.3.5.post2.

What’s New in 2.3.5.post2

This is a bugfix release. In previous versions, the built-in updating script did not update the Xformers library when the torch library was upgraded, leaving people with a version that ran on CPU only. Install this version to fix the issue so that it doesn’t happen when updating to future versions of InvokeAI 3.0.0.

As a bonus, this version allows you to apply a checkpoint VAE, such as vae-ft-mse-840000-ema-pruned.ckpt to a diffusers model, without worrying about finding the diffusers version of the VAE. From within the web Model Manager, choose the diffusers model you wish to change, press the edit button, and enter the Location of the VAE file of your choice. The field will now accept either a .ckpt file, or a diffusers directory.

Installation / Upgrading

To install 2.3.5.post2 please download the zip file at the bottom of the release notes (under “Assets”), unpack it, and then double-click to launch the script install.sh (Macintosh, Linux) or install.bat (Windows). Alternatively, you can open a command-line window and execute the installation script directly.

InvokeAI-installer-v2.3.5.post2.zip

If you are using the Xformers library, and running v2.3.5.post1 or earlier, please do not use the built-in updater to update, as it will not update xformers properly. Instead, either download the installer and ask it to overwrite the existing invokeai directory (your previously-installed models and settings will not be affected), or use the following recipe to perform a command-line install:

  1. Start the launcher script and select option # 8 - Developer’s console.
  2. Give the following command:
pip install invokeai[xformers] --use-pep517 --upgrade

If you do not use Xformers, the built-in update option (# 9) will work, as will the above command without the “[xformers]” part. From v2.3.5.post2 onward, the updater script will work properly with Xformers installed.

Developers and power users can upgrade to the current version by activating the InvokeAI environment and then using:

pip install --use-pep517 --upgrade InvokeAI

You may specify a particular version by adding the version number to the command, as in:

pip install --use-pep517 --upgrade  InvokeAI==2.3.5.post2

To upgrade to an xformers version if you are not currently using xformers, use:

pip install --use-pep517 --upgrade InvokeAI[xformers]

You can see which versions are available by going to The PyPI InvokeAI Project Page

Known Bugs in 2.3.5.post2

These are known bugs in the release.

  1. Windows Defender will sometimes raise Trojan or backdoor alerts for the codeformer.pth face restoration model, as well as the CIDAS/clipseg and runwayml/stable-diffusion-v1.5 models. These are false positives and can be safely ignored. InvokeAI performs a malware scan on all models as they are loaded. For additional security, you should use safetensors models whenever they are available.

Getting Help

Please see the InvokeAI Issues Board or the InvokeAI Discord for assistance from the development team.

Development Roadmap

This is very likely to be the last release on the v2.3 source code branch. All new features are being added to the main branch. At the current time (mid-May, 2023), the main branch is only partially functional due to a complex transition to an architecture in which all operations are implemented via flexible and extensible pipelines of “nodes”.

If you are looking for a stable version of InvokeAI, either use this release, install from the v2.3 source code branch, or use the pre-nodes tag from the main branch. Developers seeking to contribute to InvokeAI should use the head of the main branch. Please be sure to check out the dev-chat channel of the InvokeAI Discord, and the architecture documentation located at Contributing to come up to speed.

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v2.3.5…v2.3.5.post2

What’s Changed

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v2.3.5.post1…v2.3.5.post2

InvokeAI Version 2.3.5.post1

We are pleased to announce a minor update to InvokeAI with the release of version 2.3.5.post1.

What’s New in 2.3.5.post1

The major enhancement in this version is that NVIDIA users no longer need to decide between speed and reproducibility. Previously, if you activated the Xformers library, you would see improvements in speed and memory usage, but multiple images generated with the same seed and other parameters would be slightly different from each other. This is no longer the case. Relative to 2.3.5 you will see improved performance when running without Xformers, and even better performance when Xformers is activated. In both cases, images generated with the same settings will be identical.

Here are the new library versions:

LibraryVersion
Torch2.0.0
Diffusers0.16.1
Xformers0.0.19
Compel1.1.5

Other Improvements

When running the WebUI, we have reduced the number of times that InvokeAI reaches out to HuggingFace to fetch the list of embeddable Textual Inversion models. We have also caught and fixed a problem with the updater not correctly detecting when another instance of the updater is running (thanks to @pedantic79 for this).

Installation / Upgrading

To install or upgrade to InvokeAI 2.3.5.post1 please download the zip file at the bottom of the release notes (under “Assets”), unpack it, and then double-click to launch the script install.sh (Macintosh, Linux) or install.bat (Windows). Alternatively, you can open a command-line window and execute the installation script directly.

InvokeAI-installer-v2.3.5.post1.zip

If you are using the Xformers library, please do not use the built-in updater to update, as it will not update xformers properly. Instead, either download the installer and ask it to overwrite the existing invokeai directory (your previously-installed models and settings will not be affected), or use the following recipe to perform a command-line install:

  1. Start the launcher script and select option # 8 - Developer’s console.
  2. Give the following command:
pip install invokeai[xformers] --use-pep517 --upgrade

If you do not use Xformers, the built-in update option (# 9) will work, as will the above command without the “[xformers]” part.

Developers and power users can upgrade to the current version by activating the InvokeAI environment and then using pip install --use-pep517 --upgrade InvokeAI . You may specify a particular version by adding the version number to the command, as in InvokeAI==2.3.5.post1. To upgrade to an xformers version if you are not currently using xformers, use pip install --use-pep517 --upgrade InvokeAI[xformers]. You can see which versions are available by going to The PyPI InvokeAI Project Page

Known Bugs in 2.3.5.post1

These are known bugs in the release.

  1. Windows Defender will sometimes raise Trojan or backdoor alerts for the codeformer.pth face restoration model, as well as the CIDAS/clipseg and runwayml/stable-diffusion-v1.5 models. These are false positives and can be safely ignored. InvokeAI performs a malware scan on all models as they are loaded. For additional security, you should use safetensors models whenever they are available.

Getting Help

Please see the InvokeAI Issues Board or the InvokeAI Discord for assistance from the development team.

Development Roadmap

This is very likely to be the last release on the v2.3 source code branch. All new features are being added to the main branch. At the current time (mid-May, 2023), the main branch is only partially functional due to a complex transition to an architecture in which all operations are implemented via flexible and extensible pipelines of “nodes”.

If you are looking for a stable version of InvokeAI, either use this release, install from the v2.3 source code branch, or use the pre-nodes tag from the main branch. Developers seeking to contribute to InvokeAI should use the head of the main branch. Please be sure to check out the dev-chat channel of the InvokeAI Discord, and the architecture documentation located at Contributing to come up to speed.

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v2.3.4.post1…v2.3.5-rc1

What’s Changed

New Contributors

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v2.3.5…v2.3.5.post1

InvokeAI 2.3.5

We are pleased to announce a features update to InvokeAI with the release of version 2.3.5. This is currently a pre-release for community testing and bug reporting.

What’s New in 2.3.5

This release expands support for additional LoRA and LyCORIS models, upgrades diffusers to 0.15.1, and fixes a few bugs.

LoRA and LyCORIS Support Improvement

  • A number of LoRA/LyCORIS fine-tune files (those which alter the text encoder as well as the unet model) were not having the desired effect in InvokeAI. This bug has now been fixed. Full documentation of LoRA support is available at InvokeAI LoRA Support.
  • Previously, InvokeAI did not distinguish between LoRA/LyCORIS models based on Stable Diffusion v1.5 vs those based on v2.0 and 2.1, leading to a crash when an incompatible model was loaded. This has now been fixed. In addition, the web pulldown menus for LoRA and Textual Inversion selection have been enhanced to show only those files that are compatible with the currently-selected Stable Diffusion model.
  • Support for the newer LoKR LyCORIS files has been added.

Diffusers 0.15.1

  • This version updates the diffusers module to version 0.15.1 and is no longer compatible with 0.14. This provides a number of performance improvements and bug fixes.

Performance Improvements

  • When a model is loaded for the first time, InvokeAI calculates its checksum for incorporation into the PNG metadata. This process could take up to a minute on network-mounted disks and WSL mounts. This release noticeably speeds up the process.

Bug Fixes

  • The “import models from directory” and “import from URL” functionality in the console-based model installer has now been fixed.

Installation / Upgrading

To install or upgrade to InvokeAI 2.3.5 please download the zip file at the bottom of the release notes (under “Assets”), unpack it, and then double-click to launch the script install.sh (Macintosh, Linux) or install.bat (Windows). Alternatively, you can open a command-line window and execute the installation script directly. InvokeAI-installer-v2.3.5.zip

To update from versions 2.3.1 or higher, select the “update” option (choice 6) in the invoke.sh/invoke.bat launcher script and choose the option to update to 2.3.5. Alternatively, you may use the installer zip file to update. When it asks you to confirm the location of the invokeai directory, type in the path to the directory you are already using, if not the same as the one selected automatically by the installer. When the installer asks you to confirm that you want to install into an existing directory, simply indicate “yes”.

Developers and power users can upgrade to the current version by activating the InvokeAI environment and then using pip install --use-pep517 --upgrade InvokeAI . You may specify a particular version by adding the version number to the command, as in InvokeAI==2.3.5. To upgrade to an xformers version if you are not currently using xformers, use pip install --use-pep517 --upgrade InvokeAI[xformers]. You can see which versions are available by going to The PyPI InvokeAI Project Page

Known Bugs in 2.3.5

These are known bugs in the release.

  1. Windows Defender will sometimes raise Trojan or backdoor alerts for the codeformer.pth face restoration model, as well as the CIDAS/clipseg and runwayml/stable-diffusion-v1.5 models. These are false positives and can be safely ignored. InvokeAI performs a malware scan on all models as they are loaded. For additional security, you should use safetensors models whenever they are available.
  2. If the xformers memory-efficient attention module is used, each image generated with the same prompt and settings will be slightly different. xformers 0.0.19 reduces or eliminates this problem, but hasn’t been extensively tested with InvokeAI. If you wish to upgrade, you may do so by entering the InvokeAI “developer’s console” and giving the command pip install xformers==0.0.19. You may see a message about InvokeAI being incompatible with this version, which you can safely ignore. Be sure to report any unexpected behavior to the Issues pages.

Getting Help

Please see the InvokeAI Issues Board or the InvokeAI Discord for assistance from the development team.

Development Roadmap

This is very likely to be the last release on the v2.3 source code branch. All new features are being added to the main branch. At the current time (late April, 2023), the main branch is only partially functional due to a complex transition to an architecture in which all operations are implemented via flexible and extensible pipelines of “nodes”.

If you are looking for a stable version of InvokeAI, either use this release, install from the v2.3 source code branch, or use the pre-nodes tag from the main branch. Developers seeking to contribute to InvokeAI should use the head of the main branch. Please be sure to check out the dev-chat channel of the InvokeAI Discord, and the architecture documentation located at Contributing to come up to speed.

Change Log

New Contributors and Acknowledgements

  • @AbdBarho contributed the checksum performance improvements
  • @StAlKeR7779 (Sergey Borisov) contributed the LoKR support, did the diffusers 0.15 port, and cleaned up the code in multiple places.

Many thanks to these individuals, as well as @damian0815 for his contribution to this release.

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v2.3.4.post1…v2.3.5-rc1

InvokeAI Version 2.3.4.post1 - A Stable Diffusion Toolkit

We are pleased to announce a features update to InvokeAI with the release of version 2.3.4.

Update: 13 April 2024 - 2.3.4.post1 is a hotfix that corrects an installer crash resulting from an update to the upstream diffusers library. If you have recently tried to install 2.3.4 and experienced a crash relating to “crossattention,” this release will fix the issue.

What’s New in 2.3.4

This features release adds support for LoRA (Low-Rank Adaptation) and LyCORIS (Lora beYond Conventional) models, as well as some minor bug fixes.

LoRA and LyCORIS Support

LoRA files contain fine-tuning weights that enable particular styles, subjects or concepts to be applied to generated images. LyCORIS files are an extended variant of LoRA. InvokeAI supports the most common LoRA/LyCORIS format, which ends in the suffix .safetensors. You will find numerous LoRA and LyCORIS models for download at Civitai, and a small but growing number at Hugging Face. Full documentation of LoRA support is available at InvokeAI LoRA Support.( Pre-release note: this page will only be available after release)

To use LoRA/LyCORIS models in InvokeAI:

  1. Download the .safetensors files of your choice and place in /path/to/invokeai/loras. This directory was not present in earlier version of InvokeAI but will be created for you the first time you run the command-line or web client. You can also create the directory manually.

  2. Add withLora(lora-file,weight) to your prompts. The weight is optional and will default to 1.0. A few examples, assuming that a LoRA file named loras/sushi.safetensors is present:

family sitting at dinner table eating sushi withLora(sushi,0.9)
family sitting at dinner table eating sushi withLora(sushi, 0.75)
family sitting at dinner table eating sushi withLora(sushi)

Multiple withLora() prompt fragments are allowed. The weight can be arbitrarily large, but the useful range is roughly 0.5 to 1.0. Higher weights make the LoRA’s influence stronger. Negative weights are also allowed, which can lead to some interesting effects.

  1. Generate as you usually would! If you find that the image is too “crisp” try reducing the overall CFG value or reducing individual LoRA weights. As is the case with all fine-tunes, you’ll get the best results when running the LoRA on top of the model similar to, or identical with, the one that was used during the LoRA’s training. Don’t try to load a SD 1.x-trained LoRA into a SD 2.x model, and vice versa. This will trigger a non-fatal error message and generation will not proceed.

  2. You can change the location of the loras directory by passing the --lora_directory option to `invokeai.

New WebUI LoRA and Textual Inversion Buttons

This version adds two new web interface buttons for inserting LoRA and Textual Inversion triggers into the prompt as shown in the screenshot below.

old-sea-captain-annotated

Clicking on one or the other of the buttons will bring up a menu of available LoRA/LyCORIS or Textual Inversion trigger terms. Select a menu item to insert the properly-formatted withLora() or <textual-inversion> prompt fragment into the positive prompt. The number in parentheses indicates the number of trigger terms currently in the prompt. You may click the button again and deselect the LoRA or trigger to remove it from the prompt, or simply edit the prompt directly.

Currently terms are inserted into the positive prompt textbox only. However, some textual inversion embeddings are designed to be used with negative prompts. To move a textual inversion trigger into the negative prompt, simply cut and paste it.

By default the Textual Inversion menu only shows locally installed models found at startup time in /path/to/invokeai/embeddings. However, InvokeAI has the ability to dynamically download and install additional Textual Inversion embeddings from the HuggingFace Concepts Library. You may choose to display the most popular of these (with five or more likes) in the Textual Inversion menu by going to Settings and turning on “Show Textual Inversions from HF Concepts Library.” When this option is activated, the locally-installed TI embeddings will be shown first, followed by uninstalled terms from Hugging Face. See The Hugging Face Concepts Library and Importing Textual Inversion files for more information.

Minor features and fixes

This release changes model switching behavior so that the command-line and Web UIs save the last model used and restore it the next time they are launched. It also improves the behavior of the installer so that the pip utility is kept up to date.

Installation / Upgrading

To install or upgrade to InvokeAI 2.3.4 please download the zip file at the bottom of the release notes (under “Assets”), unpack it, and then double-click to launch the script install.sh (Macintosh, Linux) or install.bat (Windows). Alternatively, you can open a command-line window and execute the installation script directly.

InvokeAI-installer-v2.3.4.post1.zip

To update from versions 2.3.1 or higher, select the “update” option (choice 6) in the invoke.sh/invoke.bat launcher script and choose the option to update to 2.3.4. Alternatively, you may use the installer zip file to update. When it asks you to confirm the location of the invokeai directory, type in the path to the directory you are already using, if not the same as the one selected automatically by the installer. When the installer asks you to confirm that you want to install into an existing directory, simply indicate “yes”.

Developers and power users can upgrade to the current version by activating the InvokeAI environment and then using pip install --use-pep517 --upgrade InvokeAI . You may specify a particular version by adding the version number to the command, as in InvokeAI==2.3.4. To upgrade to an xformers version if you are not currently using xformers, use pip install --use-pep517 --upgrade InvokeAI[xformers]. You can see which versions are available by going to The PyPI InvokeAI Project Page (Pre-release note: this will only work after the official release.)

Known Bugs in 2.3.4

These are known bugs in the release.

  1. The Ancestral DPMSolverMultistepScheduler (k_dpmpp_2a) sampler is not yet implemented for diffusers models and will disappear from the WebUI Sampler menu when a diffusers model is selected.
  2. Windows Defender will sometimes raise Trojan or backdoor alerts for the codeformer.pth face restoration model, as well as the CIDAS/clipseg and runwayml/stable-diffusion-v1.5 models. These are false positives and can be safely ignored. InvokeAI performs a malware scan on all models as they are loaded. For additional security, you should use safetensors models whenever they are available.

Getting Help

Please see the InvokeAI Issues Board or the InvokeAI Discord for assistance from the development team.

Change Log

New Contributors and Acknowledgements

Many thanks to these individuals, as well as @blessedcoolant and @damian0815 for their contributions to this release.

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v2.3.3…v2.3.4rc1

InvokeAI Version 2.3.3 - A Stable Diffusion Toolkit

We are pleased to announce a bugfix update to InvokeAI with the release of version 2.3.3.

What’s New in 2.3.3

This is a bugfix and minor feature release.

Bugfixes

Since version 2.3.2 the following bugs have been fixed:

Bugs

  1. When using legacy checkpoints with an external VAE, the VAE file is now scanned for malware prior to loading. Previously only the main model weights file was scanned.
  2. Textual inversion will select an appropriate batchsize based on whether xformers is active, and will default to xformers enabled if the library is detected.
  3. The batch script log file names have been fixed to be compatible with Windows.
  4. Occasional corruption of the .next_prefix file (which stores the next output file name in sequence) on Windows systems is now detected and corrected.
  5. Support loading of legacy config files that have no personalization (textual inversion) section.
  6. An infinite loop when opening the developer’s console from within the invoke.sh script has been corrected.
  7. Documentation fixes, including a recipe for detecting and fixing problems with the AMD GPU ROCm driver.

Enhancements

  1. It is now possible to load and run several community-contributed SD-2.0 based models, including the often-requested “Illuminati” model.
  2. The “NegativePrompts” embedding file, and others like it, can now be loaded by placing it in the InvokeAI embeddings directory.
  3. If no --model is specified at launch time, InvokeAI will remember the last model used and restore it the next time it is launched.
  4. On Linux systems, the invoke.sh launcher now uses a prettier console-based interface. To take advantage of it, install the dialog package using your package manager (e.g. sudo apt install dialog).
  5. When loading legacy models (safetensors/ckpt) you can specify a custom config file and/or a VAE by placing like-named files in the same directory as the model following this example:
my-favorite-model.ckpt
my-favorite-model.yaml
my-favorite-model.vae.pt      # or my-favorite-model.vae.safetensors

Installation / Upgrading

To install or upgrade to InvokeAI 2.3.3 please download the zip file at the bottom of the release notes (under “Assets”), unpack it, and then double-click to launch the script install.sh (Macintosh, Linux) or install.bat (Windows). Alternatively, you can open a command-line window and execute the installation script directly.

InvokeAI-installer-v2.3.3.zip

To update from 2.3.1 or 2.3.2 you may use the “update” option (choice 6) in the invoke.sh/invoke.bat launcher script and choose the option to update to 2.3.3.

Alternatively, you may use the installer zip file to update. When it asks you to confirm the location of the invokeai directory, type in the path to the directory you are already using, if not the same as the one selected automatically by the installer. When the installer asks you to confirm that you want to install into an existing directory, simply indicate “yes”.

Developers and power users can upgrade to the current version by activating the InvokeAI environment and then using pip install --use-pep517 --upgrade InvokeAI . You may specify a particular version by adding the version number to the command, as in InvokeAI==2.3.3. To upgrade to an xformers version if you are not currently using xformers, use pip install --use-pep517 --upgrade InvokeAI[xformers]. You can see which versions are available by going to The PyPI InvokeAI Project Page

Known Bugs in 2.3.3

These are known bugs in the release.

  1. The Ancestral DPMSolverMultistepScheduler (k_dpmpp_2a) sampler is not yet implemented for diffusers models and will disappear from the WebUI Sampler menu when a diffusers model is selected.
  2. Windows Defender will sometimes raise Trojan or backdoor alerts for the codeformer.pth face restoration model, as well as the CIDAS/clipseg and runwayml/stable-diffusion-v1.5 models. These are false positives and can be safely ignored. InvokeAI performs a malware scan on all models as they are loaded. For additional security, you should use safetensors models whenever they are available.

What’s Changed

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v2.3.2.post1…v2.3.3-rc1

Acknowledgements

Many thanks to @psychedelicious, @blessedcoolant (Vic), @JPPhoto (Jonathan Pollack), @ebr (Eugene Brodsky) @JoshuaKimsey, @EgoringKosmos, and our crack team of Discord moderators, @gogurtenjoyer and @whosawhatsis, for all their contributions to this release.

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v2.3.2.post1…v2.3.3

InvokeAI Version 2.3.2

We are pleased to announce a bugfix update to InvokeAI with the release of version 2.3.2.

What’s New in 2.3.2

This is a bugfix and minor feature release.

Bugfixes

Since version 2.3.1 the following bugs have been fixed:

  1. Black images appearing for potential NSFW images when generating with legacy checkpoint models and both --no-nsfw_checker and --ckpt_convert turned on.
  2. Black images appearing when generating from models fine-tuned on Stable-Diffusion-2-1-base. When importing V2-derived models, you may be asked to select whether the model was derived from a “base” model (512 pixels) or the 768-pixel SD-2.1 model.
  3. The “Use All” button was not restoring the Hi-Res Fix setting on the WebUI
  4. When using the model installer console app, models failed to import correctly when importing from directories with spaces in their names. A similar issue with the output directory was also fixed.
  5. Crashes that occurred during model merging.
  6. Restore previous naming of Stable Diffusion base and 768 models.
  7. Upgraded to latest versions of diffusers, transformers, safetensors and accelerate libraries upstream. We hope that this will fix the assertion NDArray > 2**32 issue that MacOS users have had when generating images larger than 768x768 pixels. Please report back.

As part of the upgrade to diffusers, the location of the diffusers-based models has changed from models/diffusers to models/hub. When you launch InvokeAI for the first time, it will prompt you to OK a one-time move. This should be quick and harmless, but if you have modified your models/diffusers directory in some way, for example using symlinks, you may wish to cancel the migration and make appropriate adjustments.

New “Invokeai-batch” script

2.3.2 introduces a new command-line only script called invokeai-batch that can be used to generate hundreds of images from prompts and settings that vary systematically. This can be used to try the same prompt across multiple combinations of models, steps, CFG settings and so forth. It also allows you to template prompts and generate a combinatorial list like:

a shack in the mountains, photograph
a shack in the mountains, watercolor
a shack in the mountains, oil painting
a chalet in the mountains, photograph
a chalet in the mountains, watercolor
a chalet in the mountains, oil painting
a shack in the desert, photograph
...

If you have a system with multiple GPUs, or a single GPU with lots of VRAM, you can parallelize generation across the combinatorial set, reducing wait times and using your system’s resources efficiently (make sure you have good GPU cooling).

To try invokeai-batch out. Launch the “developer’s console” using the invoke launcher script, or activate the invokeai virtual environment manually. From the console, give the command invokeai-batch --help in order to learn how the script works and create your first template file for dynamic prompt generation.

Installation / Upgrading

To install or upgrade to InvokeAI 2.3.2 please download the zip file at the bottom of the release notes (under “Assets”), unpack it, and then double-click to launch the script install.sh (Macintosh, Linux) or install.bat (Windows). Alternatively, you can open a command-line window and execute the installation script directly.

InvokeAI-installer-v2.3.2.post1.zip

To update from 2.3.1 you may use the “update” option (choice 6) in the invoke.sh/invoke.bat launcher script. Alternatively, you may use the installer. When it asks you to confirm the location of the invokeai directory, type in the path to the directory you are already using, if not the same as the one selected automatically by the installer. When the installer asks you to confirm that you want to install into an existing directory, simply indicate “yes”.

Developers and power users can upgrade to the current version by activating the InvokeAI environment and then using pip install --use-pep517 --upgrade InvokeAI . You may specify a particular version by adding the version number to the command, as in InvokeAI==2.3.2. To upgrade to an xformers version if you are not currently using xformers, use pip install --use-pep517 --upgrade InvokeAI[xformers]. You can see which versions are available by going to The PyPI InvokeAI Project Page

Known Bugs in 2.3.2

These are known bugs in the release.

  1. The Ancestral DPMSolverMultistepScheduler (k_dpmpp_2a) sampler is not yet implemented for diffusers models and will disappear from the WebUI Sampler menu when a diffusers model is selected.
  2. Windows Defender will sometimes raise a Trojan alert for the codeformer.pth face restoration model. As far as we have been able to determine, this is a false positive and can be safely whitelisted.

What’s Changed

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v2.3.1…v2.3.2

Acknowledgements

Many thanks to @mauwii (Matthias Wilde), @psychedelicious, @blessedcoolant (Vic), @blhook (Pull Shark), and our crack team of Discord moderators, @gogurtenjoyer and @whosawhatsis, for all their contributions to this release.

v.2.3.1.post2

We are pleased to announce a bugfix and quality of life update to InvokeAI with the release of version 2.3.1.

What’s New in 2.3.1

This is primarily a bugfix release, but it does provide several new features that will improve the user experience.

Enhanced support for model management

InvokeAI now makes it convenient to add, remove and modify models. You can individually import models that are stored on your local system, scan an entire folder and its subfolders for models and import them automatically, and even directly import models from the internet by providing their download URLs. You also have the option of designating a local folder to scan for new models each time InvokeAI is restarted.

There are three ways of accessing the model management features:

  1. From the WebUI, click on the cube to the right of the model selection menu. This will bring up a form that allows you to import models individually from your local disk or scan a directory for models to import.

image

  1. Using the Model Installer App

Choose option (5) download and install models from the invoke launcher script to start a new console-based application for model management. You can use this to select from a curated set of starter models, or import checkpoint, safetensors, and diffusers models from a local disk or the internet. The example below shows importing two checkpoint URLs from popular SD sites and a HuggingFace diffusers model using its Repository ID. It also shows how to designate a folder to be scanned at startup time for new models to import.

Command-line users can start this app using the command invokeai-model-install.

image

  1. Using the Command Line Client (CLI)

The !install_model and !convert_model commands have been enhanced to allow entering of URLs and local directories to scan and import. The first command installs .ckpt and .safetensors files as-is. The second one converts them into the faster diffusers format before installation.

Internally InvokeAI is able to probe the contents of a .ckpt or .safetensors file to distinguish among v1.x, v2.x and inpainting models. This means that you do not need to include “inpaint” in your model names to use an inpainting model. Note that Stable Diffusion v2.x models will be autoconverted into a diffusers model the first time you use it.

Please see INSTALLING MODELS for more information on model management.

An Improved Installer Experience

The installer now launches a console-based UI for setting and changing commonly-used startup options:

image

After selecting the desired options, the installer installs several support models needed by InvokeAI’s face reconstruction and upscaling features and then launches the interface for selecting and installing models shown earlier. At any time, you can edit the startup options by launching invoke.sh/invoke.bat and entering option (6) change InvokeAI startup options

Command-line users can launch the new configure app using invokeai-configure.

This release also comes with a renewed updater. To do an update without going through a whole reinstallation, launch invoke.sh or invoke.bat and choose option (9) update InvokeAI . This will bring you to a screen that prompts you to update to the latest released version, to the most current development version, or any released or unreleased version you choose by selecting the tag or branch of the desired version.

image

Command-line users can run this interface by typing invokeai-configure

Image Symmetry Options

There are now features to generate horizontal and vertical symmetry during generation. The way these work is to wait until a selected step in the generation process and then to turn on a mirror image effect. In addition to generating some cool images, you can also use this to make side-by-side comparisons of how an image will look with more or fewer steps. Access this option from the WebUI by selecting Symmetry from the image generation settings, or within the CLI by using the options --h_symmetry_time_pct and --v_symmetry_time_pct (these can be abbreviated to --h_sym and --v_sym like all other options).

image

A New Unified Canvas Look

This release introduces a beta version of the WebUI Unified Canvas. To try it out, open up the settings dialogue in the WebUI (gear icon) and select Use Canvas Beta Layout:

image

Refresh the screen and go to to Unified Canvas (left side of screen, third icon from the top). The new layout is designed to provide more space to work in and to keep the image controls close to the image itself:

image

Model conversion and merging within the WebUI

The WebUI now has an intuitive interface for model merging, as well as for permanent conversion of models from legacy .ckpt/.safetensors formats into diffusers format. These options are also available directly from the invoke.sh/invoke.bat scripts.

An easier way to contribute translations to the WebUI

We have migrated our translation efforts to Weblate, a FOSS translation product. Maintaining the growing project’s translations is now far simpler for the maintainers and community. Please review our brief translation guide for more information on how to contribute.

Numerous internal bugfixes and performance issues

This releases quashes multiple bugs that were reported in 2.3.0. Major internal changes include upgrading to diffusers 0.13.0, and using the compel library for prompt parsing. See Detailed Change Log for a detailed list of bugs caught and squished.

Summary of InvokeAI command line scripts (all accessible via the launcher menu)

CommandDescription
invokeaiCommand line interface
invokeai --webWeb interface
invokeai-model-installModel installer with console forms-based front end
invokeai-ti --guiTextual inversion, with a console forms-based front end
invokeai-merge --guiModel merging, with a console forms-based front end
invokeai-configureStartup configuration; can also be used to reinstall support models
invokeai-updateInvokeAI software updater

Installation

To install or upgrade to InvokeAI 2.3.1, please download the zip file below, unpack it, and then double-click to launch the script install.sh (Macintosh, Linux) or install.bat (Windows). Alternatively, you can open a command-line window and execute the installation script directly.

InvokeAI-installer-v2.3.1.post2.zip

If you are upgrading from an earlier version of InvokeAI, run the installer and when it asks you to confirm the location of the invokeai directory, type in the path to the directory you are already using, if not the same as the one selected automatically by the installer. When the installer asks you to confirm that you want to install into an existing directory, simply indicate “yes”.

Developers and power users can upgrade to the current version by activating the InvokeAI environment and then using pip install --use-pep517 --upgrade InvokeAI . You may specify a particular version by adding the version number to the command, as in InvokeAI==2.3.1. To upgrade to an xformers version if you are not currently using xformers, use pip install --use-pep517 --upgrade InvokeAI[xformers]. You can see which versions are available by going to The PyPI InvokeAI Project Page

Last Feature Release on the 2.3.x Branch

This will be the last feature release on the 2.3.x branch. The development team is migrating to a new software architecture called Nodes, which will provide enhanced workflow management features as well as a much easier way for community developers to contribute to the project. We anticipate the transition taking 4-8 weeks (spring 2023). Until that time, we will be releasing bugfixes and other minor updates only.

Known Bugs in 2.3.1

These are known bugs in the release.

  1. MacOS users generating 768x768 pixel images or greater using diffusers models may experience a hard crash with assertion NDArray > 2**32 This appears to be an issue in an upstream library and currently the only workaround is to install and use legacy .ckpt/.safetensors models instead of the diffusers models. For more information on this bug, see this Issue
  2. The Ancestral DPMSolverMultistepScheduler (k_dpmpp_2a) sampler is not yet implemented for diffusers models and will disappear from the WebUI Sampler menu when a diffusers model is selected. Support will be added in the next diffusers library release.
  3. Windows Defender will sometimes raise a Trojan alert for the codeformer.pth face restoration model. As far as we have been able to determine, this is a false positive and can be safely whitelisted.
  4. InvokeAI’s memory requirements have increased modestly due to a variety of factors. For help debugging and mitigating out of memory issues, see the Troubleshooting section of the installation guide.
  5. FIXED IN 2.3.1.post1 — model merging fixed
  6. FIXED in 2.3.1.post2 — during installation, output and embeddings directories with spaces in their path names are now handled correctly.

Help

Please see the InvokeAI Issues Board or the InvokeAI Discord for assistance from the development team.

Contributors

InvokeAI is the product of the loving attention of a large number of Contributors. For this release in particular, we’d like to recognize the combined efforts of @blessedcoolant, who worked tirelessly on the model management interface despite multiple changes in the backend, and Jonathon Pollack (@JPPhoto) for working deep in the bowels of memory management and image generation. Kudos to @damian0815 and Kevin Turner (@keturn) for their improvements on model memory management and prompt parsing, respectively, and many thanks to Matthias Wild (@mauwii) and Eugene Brodsky (@ebr) for their work on package management and installation.

Last but not least, we acknowledge the tireless efforts of Kent Keirsey (@hipsterusername) for his amazing videos, outreach and team management.

What’s Changed

New Contributors

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v2.3.0…v.2.3.1-rc1

InvokeAI Version 2.3.0

We are pleased to announce a features and performance update to InvokeAI with the release of version 2.3.0.

What’s New in 2.3.0

There are multiple internal and external changes in this version of InvokeAI which greatly enhance the developer and user experiences respectively.

Migration to Stable Diffusion diffusers models

Previous versions of InvokeAI supported the original model file format introduced with Stable Diffusion 1.4. In the original format, known variously as “checkpoint”, or “legacy” format, there is a single large weights file ending with .ckpt or .safetensors. Though this format has served the community well, it has a number of disadvantages, including file size, slow loading times, and a variety of non-standard variants that require special-case code to handle. In addition, because checkpoint files are actually a bundle of multiple machine learning sub-models, it is hard to swap different sub-models in and out, or to share common sub-models. A new format, introduced by the StabilityAI company in collaboration with HuggingFace, is called diffusers and consists of a directory of individual models. The most immediate benefit of diffusers is that they load from disk very quickly. A longer term benefit is that in the near future diffusers models will be able to share common sub-models, dramatically reducing disk space when you have multiple fine-tune models derived from the same base.

When you perform a new install of version 2.3.0, you will be offered the option to install the diffusers versions of a number of popular SD models, including Stable Diffusion versions 1.5 and 2.1 (including the 768x768 pixel version of 2.1). These will act and work just like the checkpoint versions. Do not be concerned if you already have a lot of “.ckpt” or “.safetensors” models on disk! InvokeAI 2.3.0 can still load these and generate images from them without any extra intervention on your part.

To take advantage of the optimized loading times of diffusers models, InvokeAI offers options to convert legacy checkpoint models into optimized diffusers models. If you use the invokeai command line interface, the relevant commands are:

  • !convert_model — Take the path to a local checkpoint file or a URL that is pointing to one, convert it into a diffusers model, and import it into InvokeAI’s models registry file.
  • !optimize_model — If you already have a checkpoint model in your InvokeAI models file, this command will accept its short name and convert it into a like-named diffusers model, optionally deleting the original checkpoint file.
  • !import_model — Take the local path of either a checkpoint file or a diffusers model directory and import it into InvokeAI’s registry file. You may also provide the ID of any diffusers model that has been published on the HuggingFace models repository and it will be downloaded and installed automatically.

The WebGUI offers similar functionality for model management.

For advanced users, new command-line options provide additional functionality. Launching invokeai with the argument --autoconvert <path to directory> takes the path to a directory of checkpoint files, automatically converts them into diffusers models and imports them. Each time the script is launched, the directory will be scanned for new checkpoint files to be loaded. Alternatively, the --ckpt_convert argument will cause any checkpoint or safetensors model that is already registered with InvokeAI to be converted into a diffusers model on the fly, allowing you to take advantage of future diffusers-only features without explicitly converting the model and saving it to disk.

Please see INSTALLING MODELS for more information on model management in both the command-line and Web interfaces.

Support for the XFormers Memory-Efficient Crossattention Package

On CUDA (Nvidia) systems, version 2.3.0 supports the XFormers library. Once installed, thexformers package dramatically reduces the memory footprint of loaded Stable Diffusion models files and modestly increases image generation speed. xformers will be installed and activated automatically if you specify a CUDA system at install time.

The caveat with using xformers is that it introduces slightly non-deterministic behavior, and images generated using the same seed and other settings will be subtly different between invocations. Generally the changes are unnoticeable unless you rapidly shift back and forth between images, but to disable xformers and restore fully deterministic behavior, you may launch InvokeAI using the --no-xformers option. This is most conveniently done by opening the file invokeai/invokeai.init with a text editor, and adding the line --no-xformers at the bottom.

A Negative Prompt Box in the WebUI

There is now a separate text input box for negative prompts in the WebUI. This is convenient for stashing frequently-used negative prompts (“mangled limbs, bad anatomy”). The [negative prompt] syntax continues to work in the main prompt box as well.

To see exactly how your prompts are being parsed, launch invokeai with the --log_tokenization option. The console window will then display the tokenization process for both positive and negative prompts.

Model Merging

Version 2.3.0 offers an intuitive user interface for merging up to three Stable Diffusion models using an intuitive user interface. Model merging allows you to mix the behavior of models to achieve very interesting effects. To use this, each of the models must already be imported into InvokeAI and saved in diffusers format, then launch the merger using a new menu item in the InvokeAI launcher script (invoke.sh, invoke.bat) or directly from the command line with invokeai-merge --gui. You will be prompted to select the models to merge, the proportions in which to mix them, and the mixing algorithm. The script will create a new merged diffusers model and import it into InvokeAI for your use.

See MODEL MERGING for more details.

Textual Inversion Training

Textual Inversion (TI) is a technique for training a Stable Diffusion model to emit a particular subject or style when triggered by a keyword phrase. You can perform TI training by placing a small number of images of the subject or style in a directory, and choosing a distinctive trigger phrase, such as “pointillist-style”. After successful training, The subject or style will be activated by including <pointillist-style> in your prompt.

Previous versions of InvokeAI were able to perform TI, but it required using a command-line script with dozens of obscure command-line arguments. Version 2.3.0 features an intuitive TI frontend that will build a TI model on top of any diffusers model. To access training you can launch from a new item in the launcher script or from the command line using invokeai-ti --gui.

See TEXTUAL INVERSION for further details.

A New Installer Experience

The InvokeAI installer has been upgraded in order to provide a smoother and hopefully more glitch-free experience. In addition, InvokeAI is now packaged as a PyPi project, allowing developers and power-users to install InvokeAI with the command pip install InvokeAI --use-pep517. Please see Installation for details.

Developers should be aware that the pip installation procedure has been simplified and that the conda method is no longer supported at all. Accordingly, the environments_and_requirements directory has been deleted from the repository.

Installation

To install or upgrade to InvokeAI 2.3.0, please download the zip file below, unpack it, and then double-click to launch the script install.sh (Macintosh, Linux) or install.bat (Windows). Alternatively, you can open a command-line window and execute the installation script directly.

InvokeAI-installer-v2.3.0.zip

If you are upgrading from an earlier version of InvokeAI, all you have to do is to run the installer for your platform. When the installer asks you to confirm the location of the invokeai directory, type in the path to the directory you are already using, if not the same as the one selected automatically by the installer. When the installer asks you to confirm that you want to install into an existing directory, simply indicate “yes”.

Developers and power users can upgrade to the current version by activating the InvokeAI environment and then using pip install --use-pep517 --upgrade InvokeAI . You may specify a particular version by adding the version number to the command, as in InvokeAI==2.3.1. You can see which versions are available by going to The PyPI InvokeAI Project Page

Command-line name changes

All of InvokeAI’s functionality, including the WebUI, command-line interface, textual inversion training and model merging, can all be accessed from the invoke.sh and invoke.bat launcher scripts. The menu of options has been expanded to add the new functionality. For the convenience of developers and power users, we have normalized the names of the InvokeAI command-line scripts:

  • invokeai — Command-line client
  • invokeai --web — Web GUI
  • invokeai-merge --gui — Model merging script with graphical front end
  • invokeai-ti --gui — Textual inversion script with graphical front end
  • invokeai-configure — Configuration tool for initializing the invokeai directory and selecting popular starter models.

For backward compatibility, the old command names are also recognized, including invoke.py and configure-invokeai.py. However, these are deprecated and will eventually be removed.

Developers should be aware that the locations of the script’s source code has been moved. The new locations are:

  • invokeai => ldm/invoke/CLI.py
  • invokeai-configure => ldm/invoke/config/configure_invokeai.py
  • invokeai-ti=> ldm/invoke/training/textual_inversion.py
  • invokeai-merge => ldm/invoke/merge_diffusers

Developers are strongly encouraged to perform an “editable” install of InvokeAI using pip install -e . --use-pep517 in the Git repository, and then to call the scripts using their 2.3.0 names, rather than executing the scripts directly. Developers should also be aware that the several important data files have been relocated into a new directory named invokeai. This includes the WebGUI’s frontend and backend directories, and the INITIAL_MODELS.yaml files used by the installer to select starter models. Eventually all InvokeAI modules will be in subdirectories of invokeai.

Known Bugs in RC7

These are known bugs that will not be fixed prior to the release.

  1. The Ancestral DPMSolverMultistepScheduler (k_dpmpp_2a) sampler is not yet implemented for diffusers models and will disappear from the WebUI Sampler menu when a diffusers model is selected. Support will be added in the next diffusers library release.
  2. Metadata will not at first be retrieved when uploading an image into the WebGUI. The metadata will appear when the WebUI is reset and the page reloaded.
  3. The noise and threshold values are not loaded into the WebUI when the ”*” (reuse all values) button is selected.
  4. The k_heun and k_dpm_2 schedulers will appear to perform twice as many sampling steps than were requested. This is an artifact of the fact that these schedulers perform two samplings per step and is a cosmetic issue only.
  5. When launching the Textual Inversion console-based GUI, if the command window is too small, the GUI will crash with an obscure error message. Make the window larger and relaunch.

Help

Please see the InvokeAI Issues Board or the InvokeAI Discord for assistance from the development team.

Contributors

InvokeAI is the product of the loving attention of a large number of Contributors. For this release in particular, we’d like to recognize the combined efforts of Kevin Turner (@keturn), who got the diffusers port past the finish line, Eugene Brodsky (@ebr), for his work on the new installer, and Matthias Wild (@mauwii), for his many significant improvements to the testing pipeline and for setting up the system that uploads releases to the PyPi Python module repository.

We’d also like to call out Jonathon Pollack (@JPPhoto) for tirelessly testing each release candidate, @blessedcoolant and @psychedelicious for their work on the Web UI Model Manager and other UI features, and Kent Keirsey (@hipsterusername) for his amazing videos, outreach and team management.

What’s Changed

New Contributors

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v2.2.4…v2.3.0-rc5

Acknowledgements:

  • This release was supported in part by compute capacity provided by Mahdi Chaker’s “GPU Garden” cluster
  • A thousand thanks to @gogurtenjoyer and @whosawhatsis for their tireless work supporting users on the Discord server, as well as their contributions to bug finding and fixing.
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