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A language model is given the input 'The ocean is...' and calculates the conditional probability for four candidate words to be the next word. Based on the values below, which word would a model that predicts by maximizing probability choose?
- P("deep" | "The ocean is...") = 0.75
- P("cold" | "The ocean is...") = 0.15
- P("running" | "The ocean is...") = 0.09
- P("quiet" | "The ocean is...") = 0.01
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Ch.3 Prompting - 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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Using Optimized Predictions as Learning Targets
General Formula for Prediction via Maximum Probability
A language model is given the input 'The ocean is...' and calculates the conditional probability for four candidate words to be the next word. Based on the values below, which word would a model that predicts by maximizing probability choose?
- P("deep" | "The ocean is...") = 0.75
- P("cold" | "The ocean is...") = 0.15
- P("running" | "The ocean is...") = 0.09
- P("quiet" | "The ocean is...") = 0.01
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