Over the past couple of months I’ve been teaching Orbital to speak PyTorch.
Orbital’s whole pitch is that a trained model becomes SQL, so a database can run predictions on its own, with no Python process anywhere near it. Until 0.6.0, “trained model” meant scikit-learn: pipelines, trees, linear models, all .fit() in Python and then turned into a SELECT statement. It never covered what a lot of teams are actually training now: PyTorch models, not scikit-learn pipelines.
This is a companion discussion topic for the original entry at https://opensource.posit.co/blog/2026-08-17_pyorbital-0-6-0/