Softmax temperature controls the randomness of probability distributions in machine learning models. Lower values sharpen outputs, favoring high-confidence predictions, while higher values soften them, enabling exploration. Developers and data scientists use it to balance creativity and accuracy in tasks like text generation or classification, benefiting applications from chatbots to recommendation systems.
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