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Fixed typos

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Millun Atluri 2023-09-07 13:16:25 +10:00 committed by GitHub
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docs/installation/030_INSTALL_CUDA_AND_ROCM.md
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@ -68,14 +68,12 @@ Runtime Site](https://developer.nvidia.com/nvidia-container-runtime)
7. Copy everything inside the folder and save it elsewhere as a backup. 7. Copy everything inside the folder and save it elsewhere as a backup.
8. Go to __https://developer.nvidia.com/cudnn__ 8. Go to __https://developer.nvidia.com/cudnn__
9. Login or create an Account. 9. Login or create an Account.
10. Choose the newer version of Cudnnn but __read__ the Important Note __Important Note:__ 10. Choose the newer version of cuDNN. **Note:**
There is two version 11x or 12x for the differents architectures(Turing,Maxwell Etc...) of GPUs. There are two versions, 11.x or 12.x for the differents architectures(Turing,Maxwell Etc...) of GPUs.
You can find which version you should download on the link below. note that it's based on your graphics card architecture so for exemple a 4090 use the Ada Lovelace Architecture etc. You can find which version you should download from [this link](https://docs.nvidia.com/deeplearning/cudnn/support-matrix/index.html).
__https://docs.nvidia.com/deeplearning/cudnn/support-matrix/index.html__
12. Log-in Or Create An account
13. Download the latest version and extract it from the download location 13. Download the latest version and extract it from the download location
14. Find the bin folder E\cudnn-windows-x86_64-__Whatever Version__\bin 14. Find the bin folder E\cudnn-windows-x86_64-__Whatever Version__\bin
15. Copy and paste the 7 .dll files into YourInvokeFolderHere\\.venv\Lib\site-packages\torch\lib **Make sure to copy, and not move the files** 15. Copy and paste the .dll files into YourInvokeFolderHere\\.venv\Lib\site-packages\torch\lib **Make sure to copy, and not move the files**
16. If prompted, replace any existing files 16. If prompted, replace any existing files
**Notes:** **Notes:**