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Calculating Rescaled Probabilities in Text Generation
A language model is generating a sentence and, after an initial ranking, has identified the top three most likely next words. The candidates and their initial probabilities are: 'house' (0.45), 'home' (0.25), and 'building' (0.20). To proceed, the model must adjust these probabilities so they form a new, complete probability distribution before making a final selection. Calculate the new, rescaled probability for each of the three words.
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Ch.5 Inference - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Application in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
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Output Stage in Top-k Sampling
A language model is generating text and has narrowed down the next possible word to three candidates with the following initial probabilities: 'run' (0.5), 'walk' (0.2), and 'jog' (0.1). Based on the process where a final selection is made from a limited set of top candidates, which of the following actions will occur next?
Calculating Rescaled Probabilities in Text Generation
A language model is generating a sentence and has identified the three most likely next tokens as 'bright' (initial probability 0.5), 'sunny' (initial probability 0.3), and 'warm' (initial probability 0.1). According to the procedure where a final token is chosen from a limited set of top candidates, the model is guaranteed to select 'bright' as the next token after the probabilities are rescaled, because it has the highest probability.