You could consider Seldon 61 + Kubeflow 38, which has direct integration for PyTorch serving 57. Alternatively you could export your models to ONNX and use the MXNet model server 17 directly, or you could then import them into TensorFlow and use TensorFlow Serving 14, or if they are light enough you could also consider client-side inference through ONNX.js 36.
Or if your use case is more lightweight and these options seem somewhat overkill you could always make a simple server with flask or any other serving framework and call your model directly, or deploy it serverless 27 through a lambda 7/cloud 2 function.