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Sam Khoze
2024-06-21 19:08:41 -07:00
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# 👉🏼👉🏼👉🏼Please take note of the following information: This repository is compatible with MAC and Windows with CPU support at this moment. We plan to release the enabled CUDA version for Windows by June 25th. If you are testing it on your Windows machine, please ensure that the device on the nodes is set to CPU.
# 👉🏼👉🏼👉🏼Please take note of the following information: This repository is compatible and optimized for use with MAC CPU+MPS and Windows with CPU+CUDA. The installation process is not beginner-friendly for enabling CUDA [Toolkit==11.8] (https://developer.nvidia.com/cuda-11-8-0-download-archive) and [cuDNN] (https://developer.nvidia.com/cudnn-downloads?target_os=Windows&target_arch=x86_64&target_version=Agnostic&cuda_version=11) (CUDA Deep Neural Network). If you are unsure about installing CUDA, you can still use the CPU, and no CUDA installation will be necessary. However, if you are able to install CUDA correctly, the processing speed will increase significantly.
# DeepFuze
### Watch the 4k Quality Video on [YOUTUBE](https://youtu.be/PTXMNz2xyVY)
![DeepFuze Lipsync](https://github.com/SamKhoze/ComfyUI-DeepFuze/blob/main/images/LipsyncDemo.gif)
@@ -45,7 +45,7 @@ Restart your ComfyUI
## CUDA Installation
----
Install Nvidia CUDA [Toolkit==11.8](https://developer.nvidia.com/cuda-11-8-0-download-archive) and [cuDNN](https://developer.nvidia.com/cudnn-downloads?target_os=Windows&target_arch=x86_64&target_version=Agnostic&cuda_version=11) (CUDA Deep Neural Network) for Deep Learning. Ensure it is Cuda11. I found this [YOUTUBE](https://www.youtube.com/watch?v=ctQi9mU7t9o&t=655s) video useful for installation. If you have a different version of CUDA here is a [YOUTUBE](https://www.youtube.com/watch?v=I3awjvMZw9A&t=2s) link that guides you on how to uninstall your CUDA. Make sure to create paths in your Environment variable as described on [YOUTUBE VIDEO](https://www.youtube.com/watch?v=ctQi9mU7t9o&t=655s) Restart your computer after creating paths.
Install Nvidia CUDA [Toolkit==11.8](https://developer.nvidia.com/cuda-11-8-0-download-archive) and [cuDNN](https://developer.nvidia.com/cudnn-downloads?target_os=Windows&target_arch=x86_64&target_version=Agnostic&cuda_version=11) (CUDA Deep Neural Network) for Deep Learning, you must download the **cuDNN version 8.9.2.26** from the [NVIDIA DEVELOPER cuDNN Archive](https://developer.nvidia.com/rdp/cudnn-archive), if you don't have developer account you can directly download it from [GoogleDrive](https://drive.google.com/file/d/1sBGH8s7OfmkiyMwXBU2iL01bXyODfXgU/view?usp=drive_link). Ensure install **Cuda1 1.8**. I found this [YOUTUBE](https://www.youtube.com/watch?v=ctQi9mU7t9o&t=655s) video useful for installation. If you have a different version of CUDA here is a [YOUTUBE](https://www.youtube.com/watch?v=I3awjvMZw9A&t=2s) link that guides you on how to uninstall your CUDA. Make sure to create paths in your Environment variable as described on [YOUTUBE VIDEO](https://www.youtube.com/watch?v=ctQi9mU7t9o&t=655s) Restart your computer after creating paths.
Confirm your Cuda Installation, paste this code on your terminal window `nvcc --version` you should get a response like this:
```