Having issues getting PyTorch to work with CUDA on your machine? Don’t worry, you’re not alone! Here are some common solutions to the infamous “CUDA is not available” problem:
- Ensure your NVIDIA drivers are up to date. You can download them from the NVIDIA Drivers Page.
- Verify that you have the correct version of CUDA installed for your version of PyTorch. You can check compatibility on the PyTorch Previous Versions Page.
- Make sure your GPU is supported by CUDA. Check the list of CUDA-enabled GPUs.
Common Configuration Pitfalls
Misconfigurations can often hinder PyTorch from properly recognizing CUDA. Some tips:
- Confirm that the CUDA path is included in your environment variables.
- Double check your installation commands and verify no errors occurred during setup.
Get Further Help
If you’re still having trouble, consider visiting our Community Forum where other froge enthusiasts can lend a hand 🐸!