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What is Temperature?

Definition

Temperature

Temperature is a parameter that controls the randomness and creativity of text generated by an autoregressive language model during inference. Higher values increase randomness, while lower values make outputs more deterministic.

Why It Matters for AI Builders

Helps AI builders design and scale robust architectures; mastering the implementation of Temperature improves latency, accuracy, and operational efficiency for response tuning, generation formatting control, and brainstorming triggers.

Detailed Deep Dive

Temperature is a configuration parameter that controls the randomness and creativity of generative model outputs. By scaling the logits before the softmax calculation, a low temperature (near 0) forces deterministic, high-probability token selections, while a high temperature (near 1) increases token diversity.

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Frequently Asked Questions

Q:What happens at Temperature = 0?

The model becomes deterministic, choosing the single most probable word token at every step (greedy decoding).

Q:When should you use a high temperature?

During creative writing tasks, brainstorming sessions, or scenario generation where diverse outputs are desired.

Quick Facts

  • CategoryModel Operations
  • Key ApplicationResponse tuning, generation formatting control, and brainstorming triggers

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Cite This Term

Reference this definition in your articles, research, or documentation to credit this source:

[Temperature | SPIDITS Glossary](https://spidits.com/ai-glossary/temperature)

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