mirror of
https://github.com/invoke-ai/InvokeAI
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106 lines
4.2 KiB
Markdown
106 lines
4.2 KiB
Markdown
# Overview
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We offer several ways to install InvokeAI, each one suited to your
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experience and preferences. We suggest that everyone start by
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reviewing the
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[hardware](010_INSTALL_AUTOMATED.md#hardware_requirements) and
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[software](010_INSTALL_AUTOMATED.md#software_requirements)
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requirements, as they are the same across each install method. Then
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pick the install method most suitable to your level of experience and
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needs.
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See the [troubleshooting
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section](010_INSTALL_AUTOMATED.md#troubleshooting) of the automated
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install guide for frequently-encountered installation issues.
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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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### [Installation Getting Started Guide](installation)
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#### **[Automated Installer](010_INSTALL_AUTOMATED.md)**
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✅ This is the recommended installation method for first-time users.
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#### [Manual Installation](020_INSTALL_MANUAL.md)
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This method is recommended for experienced users and developers
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#### [Docker Installation](040_INSTALL_DOCKER.md)
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This method is recommended for those familiar with running Docker containers
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### Other Installation Guides
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- [PyPatchMatch](060_INSTALL_PATCHMATCH.md)
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- [XFormers](070_INSTALL_XFORMERS.md)
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- [CUDA and ROCm Drivers](030_INSTALL_CUDA_AND_ROCM.md)
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- [Installing New Models](050_INSTALLING_MODELS.md)
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## :fontawesome-solid-computer: Hardware Requirements
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### :octicons-cpu-24: System
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You wil need one of the following:
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- :simple-nvidia: An NVIDIA-based graphics card with 4 GB or more VRAM memory.
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- :simple-amd: An AMD-based graphics card with 4 GB or more VRAM memory (Linux
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only)
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- :fontawesome-brands-apple: An Apple computer with an M1 chip.
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** SDXL 1.0 Requirements*
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To use SDXL, user must have one of the following:
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- :simple-nvidia: An NVIDIA-based graphics card with 8 GB or more VRAM memory.
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- :simple-amd: An AMD-based graphics card with 16 GB or more VRAM memory (Linux
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only)
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- :fontawesome-brands-apple: An Apple computer with an M1 chip.
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### :fontawesome-solid-memory: Memory and Disk
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- At least 12 GB Main Memory RAM.
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- At least 18 GB of free disk space for the machine learning model, Python, and
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all its dependencies.
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We do **not recommend** the following video cards due to issues with their
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running in half-precision mode and having insufficient VRAM to render 512x512
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images in full-precision mode:
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- NVIDIA 10xx series cards such as the 1080ti
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- GTX 1650 series cards
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- GTX 1660 series cards
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## Installation options
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1. [Automated Installer](010_INSTALL_AUTOMATED.md)
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This is a script that will install all of InvokeAI's essential
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third party libraries and InvokeAI itself. It includes access to a
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"developer console" which will help us debug problems with you and
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give you to access experimental features.
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✅ This is the recommended option for first time users.
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2. [Manual Installation](020_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. In our hands the pip install
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is faster and more reliable, but your mileage may vary.
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Note that the conda installation method is currently deprecated and
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will not be supported at some point in the future.
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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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3. [Docker Installation](040_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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## Quick Guides
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* [Installing CUDA and ROCm Drivers](./030_INSTALL_CUDA_AND_ROCM.md)
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* [Installing XFormers](./070_INSTALL_XFORMERS.md)
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* [Installing PyPatchMatch](./060_INSTALL_PATCHMATCH.md)
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* [Installing New Models](./050_INSTALLING_MODELS.md)
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