The pytorch error message seems unambiguous: pytorch thinks you have a device with compute capability 3.5, but it requires a device with compute capability >= 3.7, so it cannot use this GPU.
If this is indeed a GPU with compute capability 3.5 (a third version of the GT 710?), you should be able to use CUDA 11 without any issues. “Deprecated” means things are fully functional but that NVIDIA will remove support “soon”, usually in the next CUDA version. So any feature deprecated in version N will likely disappear in version N+1.
Unless things changed, there should be a deviceQuery executable in the demo suite of your CUDA installation. On Windows it should be in C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\vX.Y\extras\demo_suite, where X.Y specifies your CUDA version, e.g. 10.2. deviceQuery will tell you the compute architecture of your device: CUDA Capability Major/Minor version number.
This is all pretty straight forward except for the frustrating part that marketing folks at NVIDIA repeatedly assigned the same product name to parts using different chips (from different architectures even). That’s just bad with a capital ‘B’.