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incomplete work on manual install
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docs/index.md
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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.
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## :octicons-package-dependencies-24: Installation
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This fork is supported across Linux, Windows and Macintosh. Linux users can use
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either an Nvidia-based card (with CUDA support) or an AMD card (using the ROCm
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driver).
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First time users, please see
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[Automated Installer](installation/INSTALL_AUTOMATED.md) for a walkthrough of
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getting InvokeAI up and running on your system. For alternative installation and
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upgrade instructions, please see:
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[InvokeAI Installation Overview](installation/)
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Users who wish to make use of the **PyPatchMatch** inpainting functions
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will need to perform a bit of extra work to enable this
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module. Instructions can be found at [Installing
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PyPatchMatch](installation/060_INSTALL_PATCHMATCH.md).
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If you have an NVIDIA card, you can benefit from the significant
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memory savings and performance benefits provided by Facebook Lab's
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**xFormers** module. Instructions for Linux and Windows users can be found
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at [Installing xFormers](installation/070_INSTALL_XFORMERS.md).
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## :fontawesome-solid-computer: Hardware Requirements
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### :octicons-cpu-24: System
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(invokeai) ~/InvokeAI$ python scripts/invoke.py --full_precision
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```
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## :octicons-package-dependencies-24: Installation
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This fork is supported across Linux, Windows and Macintosh. Linux users can use
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either an Nvidia-based card (with CUDA support) or an AMD card (using the ROCm
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driver).
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First time users, please see
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[Automated Installer](installation/INSTALL_AUTOMATED.md) for a walkthrough of
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getting InvokeAI up and running on your system. For alternative installation and
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upgrade instructions, please see:
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[InvokeAI Installation Overview](installation/)
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Users who wish to make use of the **PyPatchMatch** inpainting functions
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will need to perform a bit of extra work to enable this
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module. Instructions can be found at [Installing
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PyPatchMatch](installation/060_INSTALL_PATCHMATCH.md).
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If you have an NVIDIA card, you can benefit from the significant
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memory savings and performance benefits provided by Facebook Lab's
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**xFormers** module. Instructions for Linux and Windows users can be found
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at [Installing xFormers](installation/070_INSTALL_XFORMERS.md).
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## :octicons-gift-24: InvokeAI Features
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- [The InvokeAI Web Interface](features/WEB.md) -
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@ -166,89 +166,79 @@ images in full-precision mode:
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## :octicons-log-16: Latest Changes
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### v2.2.4 <small>(11 December 2022)</small>
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### v2.3.0 <small>(XX February 2023)</small>
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#### the `invokeai` directory
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#### Migration to Stable Diffusion `diffusers` models
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Previously there were two directories to worry about, the directory that
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contained the InvokeAI source code and the launcher scripts, and the `invokeai`
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directory that contained the models files, embeddings, configuration and
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outputs. With the 2.2.4 release, this dual system is done away with, and
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everything, including the `invoke.bat` and `invoke.sh` launcher scripts, now
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live in a directory named `invokeai`. By default this directory is located in
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your home directory (e.g. `\Users\yourname` on Windows), but you can select
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where it goes at install time.
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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.
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After installation, you can delete the install directory (the one that the zip
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file creates when it unpacks). Do **not** delete or move the `invokeai`
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directory!
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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.
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##### Initialization file `invokeai/invokeai.init`
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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:
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You can place frequently-used startup options in this file, such as the default
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number of steps or your preferred sampler. To keep everything in one place, this
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file has now been moved into the `invokeai` directory and is named
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`invokeai.init`.
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* `!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.
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* `!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.
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* `!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.
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#### To update from Version 2.2.3
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The WebGUI offers similar functionality for model management.
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The easiest route is to download and unpack one of the 2.2.4 installer files.
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When it asks you for the location of the `invokeai` runtime directory, respond
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with the path to the directory that contains your 2.2.3 `invokeai`. That is, if
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`invokeai` lives at `C:\Users\fred\invokeai`, then answer with `C:\Users\fred`
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and answer "Y" when asked if you want to reuse the directory.
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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.
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The `update.sh` (`update.bat`) script that came with the 2.2.3 source installer
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does not know about the new directory layout and won't be fully functional.
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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.
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#### To update to 2.2.5 (and beyond) there's now an update path.
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#### Support for the `XFormers` Memory-Efficient Crossattention Package
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As they become available, you can update to more recent versions of InvokeAI
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using an `update.sh` (`update.bat`) script located in the `invokeai` directory.
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Running it without any arguments will install the most recent version of
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InvokeAI. Alternatively, you can get set releases by running the `update.sh`
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script with an argument in the command shell. This syntax accepts the path to
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the desired release's zip file, which you can find by clicking on the green
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"Code" button on this repository's home page.
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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.
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#### Other 2.2.4 Improvements
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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.
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- Fix InvokeAI GUI initialization by @addianto in #1687
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- fix link in documentation by @lstein in #1728
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- Fix broken link by @ShawnZhong in #1736
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- Remove reference to binary installer by @lstein in #1731
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- documentation fixes for 2.2.3 by @lstein in #1740
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- Modify installer links to point closer to the source installer by @ebr in
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#1745
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- add documentation warning about 1650/60 cards by @lstein in #1753
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- Fix Linux source URL in installation docs by @andybearman in #1756
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- Make install instructions discoverable in readme by @damian0815 in #1752
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- typo fix by @ofirkris in #1755
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- Non-interactive model download (support HUGGINGFACE_TOKEN) by @ebr in #1578
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- fix(srcinstall): shell installer - cp scripts instead of linking by @tildebyte
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in #1765
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- stability and usage improvements to binary & source installers by @lstein in
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#1760
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- fix off-by-one bug in cross-attention-control by @damian0815 in #1774
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- Eventually update APP_VERSION to 2.2.3 by @spezialspezial in #1768
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- invoke script cds to its location before running by @lstein in #1805
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- Make PaperCut and VoxelArt models load again by @lstein in #1730
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- Fix --embedding_directory / --embedding_path not working by @blessedcoolant in
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#1817
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- Clean up readme by @hipsterusername in #1820
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- Optimized Docker build with support for external working directory by @ebr in
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#1544
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- disable pushing the cloud container by @mauwii in #1831
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- Fix docker push github action and expand with additional metadata by @ebr in
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#1837
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- Fix Broken Link To Notebook by @VedantMadane in #1821
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- Account for flat models by @spezialspezial in #1766
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- Update invoke.bat.in isolate environment variables by @lynnewu in #1833
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- Arch Linux Specific PatchMatch Instructions & fixing conda install on linux by
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@SammCheese in #1848
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- Make force free GPU memory work in img2img by @addianto in #1844
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- New installer by @lstein
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#### A Negative Prompt Box in the WebUI
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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.
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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.
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#### Model Merging
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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.
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See [MODEL MERGING](https://invoke-ai.github.io/InvokeAI/features/MODEL_MERGING/) for more details.
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#### Textual Inversion Training
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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.
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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`.
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See [TEXTUAL INVERSION](https://invoke-ai.github.io/InvokeAI/features/TEXTUAL_INVERSION/) for further details.
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#### A New Installer Experience
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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.
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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.
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#### Command-line name changes
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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:
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* `invokeai` -- Command-line client
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* `invokeai --web` -- Web GUI
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* `invokeai-merge --gui` -- Model merging script with graphical front end
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* `invokeai-ti --gui` -- Textual inversion script with graphical front end
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* `invokeai-configure` -- Configuration tool for initializing the `invokeai` directory and selecting popular starter models.
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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.
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Developers should be aware that the locations of the script's source code has been moved. The new locations are:
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* `invokeai` => `ldm/invoke/CLI.py`
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* `invokeai-configure` => `ldm/invoke/config/configure_invokeai.py`
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* `invokeai-ti`=> `ldm/invoke/training/textual_inversion.py`
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* `invokeai-merge` => `ldm/invoke/merge_diffusers`
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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`.
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Please see [2.3.0 Release Notes](https://github.com/invoke-ai/InvokeAI/releases/tag/v2.3.0) for further details.
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For older changelogs, please visit the
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**[CHANGELOG](CHANGELOG/#v223-2-december-2022)**.
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Block a user