Tuning Models On A Sliver

LondonResearchers tuned large models by training few weights.

It lets universities without giant computing clusters adapt frontier language models themselves.

The method trains small added matrices while freezing the base model, then uses Bayesian search instead of trial and error to tune it.

The top model scored up to 96.55% F1 on Arabic sentiment tasks, not broader ones yet.

Sources: Nature