## How to use a CUDA version that is different from PyTorch
Some features of bitsandbytes may need a newer CUDA version than regularly supported by PyTorch binaries from conda / pip. In that case you can use the following instructions to load a precompiled bitsandbytes binary that works for you.
## Installing or determining the CUDA installation
Determine the path of the CUDA version that you want to use. Common paths paths are:
```bash
/usr/local/cuda
/usr/local/cuda-XX.X
```
where XX.X is the CUDA version number.
You can also install CUDA version that you need locally with a script provided by bitsandbytes as follows:
It is best to add these lines to the `.bashrc` file to make them permanent.
If you now launch bitsandbytes with these environmental variables the PyTorch CUDA version will be overridden by the new CUDA version and a different bitsandbytes library is loaded (in this case version 117).