Glossary · Models & inference
Decoding Strategy
The algorithm that converts a model's sequence of next-token scores into selected tokens and a completed output.
Why it matters
Greedy selection, sampling, truncation, and search can produce different quality, diversity, latency, and repeatability from the same logits.
In practice
Define the task's decoding settings, stop rules, and seed behavior in the eval configuration so results can be compared fairly.
Common confusion
Decoding changes how outputs are selected; it does not change the model's trained parameters or add knowledge.
Related terms
Sources
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