Glossary · Models & inference
Top-k Sampling
A decoding method that restricts the next-token distribution to the k highest-scoring candidates, renormalizes their probabilities, and samples from that set.
Why it matters
It removes the long low-probability tail from sampling while keeping a fixed maximum candidate count.
In practice
Evaluate k together with temperature, top-p, and stop settings, and record the complete sampler configuration with generated results.
Common confusion
Top-k uses a fixed candidate count, while top-p uses a probability-mass threshold whose candidate count changes by step.
Related terms
Sources
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