TorchTPU: Google's Open Source PyTorch Back End for TPUs

Forty adjustment variables can be fine or badly overfit, depending on your rows, your outcome's rarest class, and whether you penalise the coefficients.

A curated list of ten security-tuned open models publishes one set of scores and a lot of spec sheets. Here is what you can and cannot decide from it, and how to test the rest.

The label changes with every release, so it is a poor basis for a build decision. Here is what to evaluate instead, and what tends to go wrong in production.