Top-K Sampling

Top-K sampling is a method used by Large Language Models (LLMs) during text generation to select the next word. Instead of considering the entire vocabulary, it narrows down the choices to the K most probable words predicted by the model. Low values (1-10) produce conservative, factual outputs. Medium values (20-50) balance creativity and quality. High values (50+) enable diverse, creative outputs. Use low K for technical tasks, high K for creative writing.

Visit the following resources to learn more:

• @article@Top-K Sampling: The Complete Token Selection Guide
• @video@What are the LLM’s Top-P + Top-K ?