mirror of
https://github.com/invoke-ai/InvokeAI
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55 lines
2.2 KiB
Markdown
55 lines
2.2 KiB
Markdown
---
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title: Overview
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---
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We offer several ways to install InvokeAI, each one suited to your
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experience and preferences.
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1. [InvokeAI installer](INSTALL_INVOKE.md)
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This is a installer script that installs InvokeAI and all the
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third party libraries it depends on. When a new version of
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InvokeAI is released, you will download and reinstall the new
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version.
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This installer is designed for people who want the system to "just
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work", don't have an interest in tinkering with it, and do not
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care about upgrading to unreleased experimental features.
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2. [Source code installer](INSTALL_SOURCE.md)
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This is a script that will install InvokeAI and all its essential
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third party libraries. In contrast to the previous installer, it
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includes access to a "developer console" which will allow you to
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access experimental features on the development branch.
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This method is recommended for individuals who are wish to stay
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on the cutting edge of InvokeAI development and are not afraid
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of occasional breakage.
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3. [Manual Installation](INSTALL_MANUAL.md)
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In this method you will manually run the commands needed to install
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InvokeAI and its dependencies. We offer two recipes: one suited to
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those who prefer the `conda` tool, and one suited to those who prefer
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`pip` and Python virtual environments.
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This method is recommended for users who have previously used `conda`
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or `pip` in the past, developers, and anyone who wishes to remain on
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the cutting edge of future InvokeAI development and is willing to put
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up with occasional glitches and breakage.
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4. [Docker Installation](INSTALL_DOCKER.md)
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We also offer a method for creating Docker containers containing
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InvokeAI and its dependencies. This method is recommended for
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individuals with experience with Docker containers and understand
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the pluses and minuses of a container-based install.
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5. [Jupyter Notebooks Installation](INSTALL_JUPYTER.md)
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This method is suitable for running InvokeAI on a Google Colab
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account. It is recommended for individuals who have previously
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worked on the Colab and are comfortable with the Jupyter notebook
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environment.
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