https://nalar.dev/tags/sampling/ Recent content in Sampling on Nalar Hugo en-us Wed, 09 Sep 2026 00:00:00 +0700 https://nalar.dev/control-llm-randomness-with-temperature-top-k-and-top-p/ Wed, 09 Sep 2026 00:00:00 +0700 https://nalar.dev/control-llm-randomness-with-temperature-top-k-and-top-p/ <p>A language model does not normally produce a single inevitable next token. Given a prefix, it assigns scores to many possible tokens. A decoding algorithm then decides how to turn those scores into the next output.</p> <p>That last step matters. If you sample too freely, a model can drift into unlikely continuations. If you restrict sampling too aggressively, outputs can become repetitive or lose useful variation. Parameters such as <strong>temperature</strong>, <strong>top-k</strong>, and <strong>top-p</strong> control different parts of this trade-off, so treating them as interchangeable &ldquo;creativity settings&rdquo; leads to confusing results.</p>