> It's kinda interesting because this is a clear case where the model must be thinking beyond the next token
I don't see how you get to this conclusion. From all the training data it has seen, "an" is the most probable next word after "I climbed up the tree and picked up". The network does not need to know anything about the apple at this point.
Then, the next word is "apple" (with an even higher probability I guess).
I don't see how you get to this conclusion. From all the training data it has seen, "an" is the most probable next word after "I climbed up the tree and picked up". The network does not need to know anything about the apple at this point. Then, the next word is "apple" (with an even higher probability I guess).