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InferenceMultiple choiceMedium

Your model writes stories with beam search, and after a few sentences the text loops. Sampling from the full distribution fixes the loops but occasionally picks a very unlikely word and derails.

Some next-word distributions are flat with many good choices; others are sharply peaked on a few.

How would you decode to keep the text varied without falling into the unreliable tail?