LLM Temperature Explained: How It Controls AI Output and Randomness
Note: This article has some prerequisites. I recommend reading my previous article on Tokens in LLMs first, as some terms used here may be confusing if you haven't learned them yet. I'm sharing the link below. Go through it and come back when you're done. We'll be waiting for you. 😊 What Are Tokens in LLMs? Complete Guide to Tokenization Temperature in LLMs: Complete Beginner's Guide Temperature is a setting used in Large Language Models (LLMs) that controls how strongly the model prefers the most likely next token when generating text. 1. What is Temperature? Temperature controls how strongly an LLM prefers the most likely next token. Low temperature: The model strongly prefers the most likely token. High temperature: The model gives less-likely tokens more opportunity to be selected. 2. How Does an LLM Choose a Token? Suppose we give the model: "The cat is" The model may calculate...
