An engineer is examining the input to a large language model that has been adapted for a new task. The input is visualized as a single sequence of vectors: [P1, P2, P3, P4, E1, E2, E3, E4, E5], where the 'P' vectors are adjusted during training and the 'E' vectors remain unchanged. Based on this structure, what is the most accurate analysis of this input method?
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Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
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An engineer is examining the input to a large language model that has been adapted for a new task. The input is visualized as a single sequence of vectors: [P1, P2, P3, P4, E1, E2, E3, E4, E5], where the 'P' vectors are adjusted during training and the 'E' vectors remain unchanged. Based on this structure, what is the most accurate analysis of this input method?
An engineer is designing the input for a large language model using a method where a small set of new, trainable vectors are prepended to the standard, frozen vectors of the input text. Below are four potential visual representations of this combined input sequence. Which diagram incorrectly illustrates this input composition?
Constructing a Prompt-Tuned Input Sequence