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@ -133,11 +133,12 @@ If you don't use Anaconda, type `python -V` in terminal to make sure python>=3.9
Run `nvidia-smi` in a terminal. If this results in an error, your GPU is probably not compatible with CUDA. If not, note the "CUDA version": it is the latest version your driver is compatible with (more information [on this post](https://stackoverflow.com/questions/60987997/why-torch-cuda-is-available-returns-false-even-after-installing-pytorch-with)).
Then go to the [ONNXruntime requirement page](https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#requirements), note the latest compatible CUDA and cuDNN requirements. Finally, go to the [pyTorch website]( https://pytorch.org/get-started/locally) and install the latest version that satisfies these requirements (beware that torch 2.4 ships with cuDNN 9, while torch 2.3 installs cuDNN 8). You may need to opt for a previous version, downloadable [there](https://pytorch.org/get-started/previous-versions/). For example:
Then go to the [ONNXruntime requirement page](https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#requirements), note the latest compatible CUDA and cuDNN requirements. Next, go to the [pyTorch website](https://pytorch.org/get-started/previous-versions/) and install the latest version that satisfies these requirements (beware that torch 2.4 ships with cuDNN 9, while torch 2.3 installs cuDNN 8). For example:
``` cmd
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124
```
Then install ONNX Runtime with GPU support:
Finally, install ONNX Runtime with GPU support:
```
pip install onnxruntime-gpu
```