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Update 030_INSTALL_CUDA_AND_ROCM.md
Added Extra step and clarification on how to choose between 11x or 12x update for Cudnnn dll
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@ -66,12 +66,16 @@ Runtime Site](https://developer.nvidia.com/nvidia-container-runtime)
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5. Click on Torch directory - e.g., YourInvokeFolderHere\InvokeAI\\.venv\Lib\site-packages\torch
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6. Click on the lib folder - e.g., YourInvokeFolderHere\\.venv\Lib\site-packages\torch\lib
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7. Copy everything inside the folder and save it elsewhere as a backup.
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8. Go to https://developer.nvidia.com/cudnn
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9. Log-in Or Create An account
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10. Download the latest version and extract it from the download location
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12. Find the bin folder E\cudnn-windows-x86_64-__Whatever Version__\bin
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13. Copy and paste the 7 .dll files into YourInvokeFolderHere\\.venv\Lib\site-packages\torch\lib **Make sure to copy, and not move the files**
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14. If prompted, replace any existing files
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8. Go to __https://developer.nvidia.com/cudnn__
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9. Login or create an Account.
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10. Choose the newer version of Cudnnn but __read__ the Important Note __Important Note:__
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There is two version 11x or 12x for the differents architectures(Turing,Maxwell Etc...) of GPUs.
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You can find which version you should download here note that it's based on your graphics card architecture so for exemple a 4090 use the Ada Lovelace Architecture etc.: __https://docs.nvidia.com/deeplearning/cudnn/support-matrix/index.html__
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11. Log-in Or Create An account
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12. Download the latest version and extract it from the download location
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13. Find the bin folder E\cudnn-windows-x86_64-__Whatever Version__\bin
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14. Copy and paste the 7 .dll files into YourInvokeFolderHere\\.venv\Lib\site-packages\torch\lib **Make sure to copy, and not move the files**
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15. If prompted, replace any existing files
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**Notes:**
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* If no change is seen or any issues are encountered, follow the same steps as above and paste the torch/lib backup folder you made earlier and replace it. If you didn't make a backup, you can also uninstall and reinstall torch through the command line to repair this folder.
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