Not sure how. If I have, e.g. a PyTorch model how do I deploy it for streaming data without having to rewrite it in another framework? (e.g. stateful convolutions, ability to receive an arbitrary number of samples as input, etc). It's doable, but mostly amounts to rewriting your model. This should be automated.

Streaming inference support. Deploying ML models to work in real-time with little latency is a pain.