Temperature

Temperature is a parameter used in language models that controls the randomness of the generated text. A higher temperature value (e.g., 1.0) leads to more diverse and unpredictable outputs, as the model is more likely to sample less probable words. Conversely, a lower temperature value (e.g., 0.2) yields more deterministic, conservative outputs, favoring the most likely words according to the model's training data. Essentially, it influences the probability distribution from which the next word is selected.

Visit the following resources to learn more:

• @article@What Temperature Means in Natural Language Processing and AI
• @article@What is LLM Temperature? - IBM
• @article@How Temperature Settings Transform Your AI Agent's Responses