pip install cudatoolkit pytorch

Title: Installing PyTorch with CUDA Toolkit using pip
Introduction:
PyTorch is a popular deep learning framework that allows developers to build and train neural networks. If you have a compatible NVIDIA GPU, you can leverage CUDA, a parallel computing platform, to accelerate PyTorch computations. This tutorial will guide you through the process of installing PyTorch with CUDA Toolkit using the pip package manager.
Prerequisites:
Steps:
Follow the installation instructions provided on the CUDA Toolkit download page for your specific operating system.
After installing the CUDA Toolkit, verify the installation by checking the CUDA version. Open a terminal or command prompt and run the following command:
This command should display information about the installed CUDA version.
Now that you have the CUDA Toolkit installed, you can proceed to install PyTorch with CUDA support using pip. Open a terminal or command prompt and run the following command:
To verify that PyTorch is installed correctly with CUDA support, open a Python interpreter or create a Python script and run the following commands:
If everything is set up correctly, the output should indicate the PyTorch version, CUDA availability, and CUDA version.
Congratulations! You have successfully installed PyTorch with CUDA Toolkit support using pip. You are now ready to develop and run deep learning applications that take advantage of GPU acceleration.
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