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top p

Applied AI interview questions tagged top p, across every topic.

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Concepts behind "top p"

The curriculum that explains the ideas these questions test.

Core
🧠 Foundations of LLMs & GenAISign in
Temperature and SamplingAt each step a model outputs a probability distribution over the next token; how you pick from it is decoding. Temperature reshapes the distribution (low sharpens toward the most likely token, high flattens it), while top-k and top-p (nucleus) truncate the tail before sampling. The choice sets the trade-off between deterministic, focused output and diverse, creative output. Applied-AI interviews probe it because the right decoding settings differ sharply between factual/extraction tasks and creative ones, and because reproducibility depends on them.
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