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7 LLM Generation Parameters—What They Do and How to Tune Them?

Summary by MarkTechPost
Tuning LLM outputs is largely a decoding problem: you shape the model’s next-token distribution with a handful of sampling controls—max tokens (caps response length under the model’s context limit), temperature (logit scaling for more/less randomness), top-p/nucleus and top-k (truncate the candidate set by probability mass or rank), frequency and presence penalties (discourage repetition or encourage novelty), and stop sequences (hard terminatio…
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MarkTechPost broke the news in on Tuesday, October 14, 2025.
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