---
title: Home
---
# :octicons-home-16: Home
[](https://github.com/invoke-ai/InvokeAI)
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InvokeAI is an
implementation of Stable Diffusion, the open source text-to-image and
image-to-image generator. It provides a streamlined process with various new
features and options to aid the image generation process. It runs on Windows,
Mac and Linux machines, and runs on GPU cards with as little as 4 GB or RAM.
**Quick links**: [Discord Server]
[Code and Downloads] [Bug Reports] [Discussion, Ideas &
Q&A]
!!! note
This fork is rapidly evolving. Please use the [Issues tab](https://github.com/invoke-ai/InvokeAI/issues) to report bugs and make feature requests. Be sure to use the provided templates. They will help aid diagnose issues faster.
## :fontawesome-solid-computer: Hardware Requirements
### :octicons-cpu-24: System
You wil need one of the following:
- :simple-nvidia: An NVIDIA-based graphics card with 4 GB or more VRAM memory.
- :simple-amd: An AMD-based graphics card with 4 GB or more VRAM memory (Linux
only)
- :fontawesome-brands-apple: An Apple computer with an M1 chip.
We do **not recommend** the following video cards due to issues with their
running in half-precision mode and having insufficient VRAM to render 512x512
images in full-precision mode:
- NVIDIA 10xx series cards such as the 1080ti
- GTX 1650 series cards
- GTX 1660 series cards
### :fontawesome-solid-memory: Memory and Disk
- At least 12 GB Main Memory RAM.
- At least 18 GB of free disk space for the machine learning model, Python,
and all its dependencies.
## :octicons-package-dependencies-24: Installation
This fork is supported across Linux, Windows and Macintosh. Linux users can use
either an Nvidia-based card (with CUDA support) or an AMD card (using the ROCm
driver).
### [Installation Getting Started Guide](installation)
#### [Automated Installer](installation/010_INSTALL_AUTOMATED.md)
This method is recommended for 1st time users
#### [Manual Installation](installation/020_INSTALL_MANUAL.md)
This method is recommended for experienced users and developers
#### [Docker Installation](installation/040_INSTALL_DOCKER.md)
This method is recommended for those familiar with running Docker containers
### Other Installation Guides
- [PyPatchMatch](installation/060_INSTALL_PATCHMATCH.md)
- [XFormers](installation/070_INSTALL_XFORMERS.md)
- [CUDA and ROCm Drivers](installation/030_INSTALL_CUDA_AND_ROCM.md)
- [Installing New Models](installation/050_INSTALLING_MODELS.md)
## :octicons-gift-24: InvokeAI Features
### The InvokeAI Web Interface
- [WebUI overview](features/WEB.md)
- [WebUI hotkey reference guide](features/WEBUIHOTKEYS.md)
- [WebUI Unified Canvas for Img2Img, inpainting and outpainting](features/UNIFIED_CANVAS.md)
- [Visual Manual for InvokeAI v2.3.1](https://docs.google.com/presentation/d/e/2PACX-1vSE90aC7bVVg0d9KXVMhy-Wve-wModgPFp7AGVTOCgf4xE03SnV24mjdwldolfCr59D_35oheHe4Cow/pub?start=false&loop=true&delayms=60000) (contributed by Statcomm)
### The InvokeAI Command Line Interface
- [Command Line Interace Reference Guide](features/CLI.md)
### Image Management
- [Image2Image](features/IMG2IMG.md)
- [Inpainting](features/INPAINTING.md)
- [Outpainting](features/OUTPAINTING.md)
- [Adding custom styles and subjects](features/CONCEPTS.md)
- [Using LoRA models](features/LORAS.md)
- [Upscaling and Face Reconstruction](features/POSTPROCESS.md)
- [Embiggen upscaling](features/EMBIGGEN.md)
- [Other Features](features/OTHER.md)
### Model Management
- [Installing](installation/050_INSTALLING_MODELS.md)
- [Model Merging](features/MODEL_MERGING.md)
- [Adding custom styles and subjects via embeddings](features/CONCEPTS.md)
- [Textual Inversion](features/TEXTUAL_INVERSION.md)
- [Not Safe for Work (NSFW) Checker](features/NSFW.md)
### Prompt Engineering
- [Prompt Syntax](features/PROMPTS.md)
- [Generating Variations](features/VARIATIONS.md)
## :octicons-log-16: Latest Changes
### v2.3.3 (29 March 2023)
#### Bug Fixes
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. An infinite loop when opening the developer's console from within the `invoke.sh` script has been corrected.
#### Enhancements
1. It is now possible to load and run several community-contributed SD-2.0 based models, including the infamous "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
```
### v2.3.2 (13 March 2023)
#### 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.
### v2.3.1 (26 February 2023)
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.
2. **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`.
3. **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](https://invoke-ai.github.io/InvokeAI/installation/050_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:
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.
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).
#### 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_:
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:
#### 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](https://hosted.weblate.org/engage/invokeai/), 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](https://github.com/invoke-ai/InvokeAI/blob/v2.3.1/docs/other/TRANSLATION.md) 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](#full-change-log) for a detailed list of bugs caught and squished.
#### Summary of InvokeAI command line scripts (all accessible via the launcher menu)
| Command | Description |
|--------------------------|---------------------------------------------------------------------|
| `invokeai` | Command line interface |
| `invokeai --web` | Web interface |
| `invokeai-model-install` | Model installer with console forms-based front end |
| `invokeai-ti --gui` | Textual inversion, with a console forms-based front end |
| `invokeai-merge --gui` | Model merging, with a console forms-based front end |
| `invokeai-configure` | Startup configuration; can also be used to reinstall support models |
| `invokeai-update` | InvokeAI software updater |
### v2.3.0 (9 February 2023)
#### 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](https://huggingface.co/models?pipeline_tag=text-to-image&sort=downloads)
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 ` 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](https://invoke-ai.github.io/InvokeAI/installation/050_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, the`xformers` 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](https://invoke-ai.github.io/InvokeAI/features/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 `` 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](https://invoke-ai.github.io/InvokeAI/features/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](#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.
#### 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`.
Please see
[2.3.0 Release Notes](https://github.com/invoke-ai/InvokeAI/releases/tag/v2.3.0)
for further details. For older changelogs, please visit the
**[CHANGELOG](CHANGELOG/#v223-2-december-2022)**.
## :material-target: Troubleshooting
Please check out our
**[:material-frequently-asked-questions: Troubleshooting Guide](installation/010_INSTALL_AUTOMATED.md#troubleshooting)**
to get solutions for common installation problems and other issues.
## :octicons-repo-push-24: Contributing
Anyone who wishes to contribute to this project, whether documentation,
features, bug fixes, code cleanup, testing, or code reviews, is very much
encouraged to do so. If you are unfamiliar with how to contribute to GitHub
projects, here is a
[Getting Started Guide](https://opensource.com/article/19/7/create-pull-request-github).
A full set of contribution guidelines, along with templates, are in progress,
but for now the most important thing is to **make your pull request against the
"development" branch**, and not against "main". This will help keep public
breakage to a minimum and will allow you to propose more radical changes.
## :octicons-person-24: Contributors
This fork is a combined effort of various people from across the world.
[Check out the list of all these amazing people](other/CONTRIBUTORS.md). We
thank them for their time, hard work and effort.
## :octicons-question-24: Support
For support, please use this repository's GitHub Issues tracking service. Feel
free to send me an email if you use and like the script.
Original portions of the software are Copyright (c) 2022-23 by
[The InvokeAI Team](https://github.com/invoke-ai).
## :octicons-book-24: Further Reading
Please see the original README for more information on this software and
underlying algorithm, located in the file
[README-CompViz.md](other/README-CompViz.md).
