The raw output of a transformer model is a list of logits, confidence scores for each token in its vocabulary. It's only deterministic in this sense (same input = same scores). But it can easily assign equal scores to 1 and 0 and zero to other tokens, and you'll have to sample it randomly to produce the result. Whether you consider it external or internal doesn't matter, transformers are inherently probabilistic by design. Randomness is all they produce. And typically they aren't trained with the case of temperature 0 and greedy sampling in mind.