Cuda / DirectML question

Hi there, you made fantastic framework for llms. But what I find very confusing is how to run this on cuda and direct ml. I simply don't know how to do it in C#..

I there any example? Second question is, do I have to provide different model per cuda, cpu and directml or can it run seamlessly? Or is there a way to convert model to support all or combination of providers? as far as I know onnx it self provides seamles support that's why it's a bit confusing.

My use case is to deploy to user's device a model and based on his capabilities to choose the provider which can provide best performance. But not in the opposite direction, because I expect my user to know nothing about the ML it self.

Thank you ✌️

The issue names no repository files, tests, or entry points. First determine whether C# examples and provider-selection guidance belong in the repository, then document the supported CUDA, CPU, and DirectML workflow and verify the examples against the relevant runtime setup.

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