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AI & Machine Learning · Intermediate

Top-p Sampling

Nucleus sampling: choose the next token from the smallest set whose cumulative probability exceeds p.

Definition

Top-p adapts the candidate pool to the model's confidence: few tokens when confident, more when uncertain. Common values are 0.9 to 0.95. Vendors usually advise adjusting temperature or top-p, not both.

Exam tip

Lowering top-p makes output more focused; it narrows the candidate tokens.

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