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A team is tasked with adapting a large, pre-trained language model to summarize legal documents. One developer designs a method where each summarization request includes a detailed set of instructions and examples of high-quality summaries, which are provided to the original, unchanged model. Another developer uses a large dataset of legal documents and their corresponding summaries to make small, permanent adjustments to the model's internal configuration before deploying it. What is the most significant difference between these two approaches regarding the pre-trained model itself?
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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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A team is tasked with adapting a large, pre-trained language model to summarize legal documents. One developer designs a method where each summarization request includes a detailed set of instructions and examples of high-quality summaries, which are provided to the original, unchanged model. Another developer uses a large dataset of legal documents and their corresponding summaries to make small, permanent adjustments to the model's internal configuration before deploying it. What is the most significant difference between these two approaches regarding the pre-trained model itself?
Analysis of Activation Function Choice in Transformer Architectures
A researcher is preparing a training example for a language model that uses a prefix-based objective. The goal is for the model to learn to complete the sentence 'The sun is shining brightly in the sky.' after being given the first three words as context. Which of the following options correctly partitions the sentence into a prefix and a subsequent sequence for this task?