> Completely bespoke models are typically trained in Python using tools like TensorFlow, JAX or PyTorch that don't have real non-Python alternatives
The article outlines some interesting ways to evade this problem. What's the latest thinking on robustly addressing it, e.g. are there any approaches for executing inference on a tf or pytorch model from within a golang process, no sidecar required?
The article outlines some interesting ways to evade this problem. What's the latest thinking on robustly addressing it, e.g. are there any approaches for executing inference on a tf or pytorch model from within a golang process, no sidecar required?