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Temperature
What is temperature?
Temperature controls randomness in token selection. Lower values make output more deterministic and repetitive; higher values make it more varied and more likely to be wrong. For extraction and classification it should be at or near zero.
The most common misconfiguration in production is a default temperature left in place on a task that wanted determinism. Structured extraction at temperature 0.7 produces occasional inventive nonsense for no benefit.
It also makes evaluation harder: a non-zero temperature means the same input can produce different outputs, so results have to be averaged over runs to be comparable.
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