ML
Classifier-Free Guidance: The Guidance Scale Is an Exponent on an Implicit Classifier
Classifier-free guidance (CFG) trains a conditional generative model with condition dropout, so one network can predict both with and without the conditioning signal. At sampling time the two predictions are combined by extrapolating along their difference, scaled by a guidance weight. Nearly every modern conditional generator exposes that weight: