Hi everyone, I’m fine-tuning XLNet for generation.  For training, I’ve edited the permutation_mask to predict the target sequence one word at a time.  I’m evaluating my trained model and am trying to decide between trainer.evaluate() and model.generate().  Running the same input/model with both methods yields different predicted tokens.  Is it correct that trainer.evaluate() is not set up for sequential generation?  I’ll switch my evaluation code to use model.generate() if that’s the case. Thanks for the help!