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A standard 12-layer language model and a depth-adaptive 12-layer language model are both used for inference on two different input sentences. Sentence 1 is 'The sky is blue.' Sentence 2 is 'The philosophical underpinnings of existentialism challenge traditional notions of predetermined essence.' How would the computational cost for processing these two sentences likely compare between the two models?
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Ch.1 Pre-training - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
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Analysis in Bloom's Taxonomy
Cognitive Psychology
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Model Selection for Resource-Constrained Deployment
A standard 12-layer language model and a depth-adaptive 12-layer language model are both used for inference on two different input sentences. Sentence 1 is 'The sky is blue.' Sentence 2 is 'The philosophical underpinnings of existentialism challenge traditional notions of predetermined essence.' How would the computational cost for processing these two sentences likely compare between the two models?
A depth-adaptive language model is processing the sentence: 'The intricate legal arguments presented by the defense were compelling.' Which of the following best explains why the token for 'the' would likely exit the model's layers earlier than the token for 'intricate'?