Match each parameter-efficient adaptation method to the description of how it modifies a pre-trained model's architecture.
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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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Analysis in Bloom's Taxonomy
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Analysis of a Model Adaptation Strategy
An engineer is adapting a pre-trained language model for a new task. They want to add a small number of trainable vectors to guide the model's behavior without changing any of the original model weights. What is the fundamental architectural difference between a strategy that adds these vectors only to the input embedding layer versus one that adds them to the input of every transformer layer?
Related
Analysis of a Model Adaptation Strategy
An engineer is adapting a pre-trained language model for a new task. They want to add a small number of trainable vectors to guide the model's behavior without changing any of the original model weights. What is the fundamental architectural difference between a strategy that adds these vectors only to the input embedding layer versus one that adds them to the input of every transformer layer?