Which LLM parameter limits word selection at each generation step to the K most probable tokens?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Todd Lammle: 'Imagine you're building a chatbot and this exact situation comes up — top k is your go-to move. Top K sampling restricts the pool of candidate tokens at each step to the K most probable options; reducing but not eliminating randomness. This is a classic Domain 4: Integrate with watsonx concept you'll want locked in before exam day.'
Full explanation below image
Full Explanation
Top K sampling restricts the pool of candidate tokens at each step to the K most probable options; reducing but not eliminating randomness. Temperature scales probability distributions. Top P uses a cumulative probability threshold instead of a fixed count. Max new tokens caps total output length. The correct answer, "Top K", directly satisfies the scenario because it aligns with watsonx Assistant's design principles and the specific capability being tested. The incorrect options ("Temperature", "Top P", "Max new tokens") may appear relevant but each misses a key requirement or introduces a step that is either unnecessary or belongs to a different workflow. Mastering the distinction between these approaches is essential for effective watsonx Assistant implementations and is a core focus of the Domain 4: Integrate with watsonx section of the certification exam.