mirror of
https://github.com/invoke-ai/InvokeAI
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97 lines
4.0 KiB
Markdown
97 lines
4.0 KiB
Markdown
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# Installation Troubleshooting
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!!! info "How to Reinstall"
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Many issues can be resolved by re-installing the application. You won't lose any data by re-installing. We suggest downloading the [latest release] and using it to re-install the application.
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When you run the installer, you'll have an option to select the version to install. If you aren't ready to upgrade, you choose the current version to fix a broken install.
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If the troubleshooting steps on this page don't get you up and running, please either [create an issue] or hop on [discord] for help.
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## OSErrors on Windows while installing dependencies
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During a zip file installation or an online update, installation stops
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with an error like this:
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{:width="800px"}
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To resolve this, re-install the application as described above.
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## Stable Diffusion XL generation fails after trying to load UNet
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InvokeAI is working in other respects, but when trying to generate
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images with Stable Diffusion XL you get a "Server Error". The text log
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in the launch window contains this log line above several more lines of
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error messages:
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`INFO --> Loading model:D:\LONG\PATH\TO\MODEL, type sdxl:main:unet`
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This failure mode occurs when there is a network glitch during
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downloading the very large SDXL model.
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To address this, first go to the Model Manager and delete the
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Stable-Diffusion-XL-base-1.X model. Then, click the HuggingFace tab,
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paste the Repo ID stabilityai/stable-diffusion-xl-base-1.0 and install
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the model.
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### Package dependency conflicts
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If you have previously installed InvokeAI or another Stable Diffusion
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package, the installer may occasionally pick up outdated libraries and
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either the installer or `invoke` will fail with complaints about
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library conflicts.
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To resolve this, re-install the application as described above.
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### InvokeAI runs extremely slowly on Linux or Windows systems
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The most frequent cause of this problem is when the installation
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process installed the CPU-only version of the torch machine-learning
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library, rather than a version that takes advantage of GPU
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acceleration. To confirm this issue, look at the InvokeAI startup
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messages. If you see a message saying ">> Using device CPU", then
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this is what happened.
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To resolve this, re-install the application as described above. Be sure to select the correct GPU device.
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### Invalid configuration file
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Everything seems to install ok, you get a `ValidationError` when starting up the app.
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This is caused by an invalid setting in the `invokeai.yaml` configuration file. The error message should tell you what is wrong.
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Check the [configuration docs] for more detail about the settings and how to specify them.
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### Out of Memory Issues
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The models are large, VRAM is expensive, and you may find yourself
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faced with Out of Memory errors when generating images. Here are some
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tips to reduce the problem:
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#### 4 GB of VRAM
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This should be adequate for 512x512 pixel images using Stable Diffusion 1.5
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and derived models, provided that you do not use the NSFW checker. It won't be loaded unless you go into the UI settings and turn it on.
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If you are on a CUDA-enabled GPU, we will automatically use xformers or torch-sdp to reduce VRAM requirements, though you can explicitly configure this. See the [configuration docs].
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#### 6 GB of VRAM
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This is a border case. Using the SD 1.5 series you should be able to
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generate images up to 640x640 with the NSFW checker enabled, and up to
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1024x1024 with it disabled.
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If you run into persistent memory issues there are a series of
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environment variables that you can set before launching InvokeAI that
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alter how the PyTorch machine learning library manages memory. See
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<https://pytorch.org/docs/stable/notes/cuda.html#memory-management> for
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a list of these tweaks.
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#### 12 GB of VRAM
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This should be sufficient to generate larger images up to about 1280x1280.
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[create an issue]: https://github.com/invoke-ai/InvokeAI/issues
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[discord]: https://discord.gg/ZmtBAhwWhy
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[configuration docs]: ../features/CONFIGURATION.md
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