In our team, We serve PyTorch models in production using libtorch. A C++ library for loading models. You can easily call the C++ code in Go if you wrap it in a C interface.

Last I checked there was basically zero serving story for pytorch. The trade off seems all to common, tensorflow optimizes for enormous production applications first while pytorch optimizes for developer ease first.

If you are trying to apply one of these libraries to a production system that doesn’t get a lot of throughput you probably shouldn’t be using them (try a linear model first). If you have a high throughput application you probably want tensorflow and just deal with the shittyness.