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BERT Input Representation: Single and Paired Sentences
BERT models are built to represent either individual sentences or pairs of sentences, equipping them to tackle a variety of downstream language understanding problems. When a task requires handling two sentences simultaneously, the input is arranged as a single combined sequence containing both sentences, typically denoted as and .
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References
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Reference of Foundations of Large Language Models Course
Reference of Foundations of Large Language Models Course
Reference of Foundations of Large Language Models Course
Reference of Foundations of Large Language Models Course
Tags
What is BERT?
Data Science
Ch.1 Pre-training - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Learn After
Next Sentence Prediction (NSP)
A language representation model is designed with the flexibility to process either a single piece of text or a pair of texts as its input, allowing it to be adapted for a wide variety of tasks. Which of the following tasks would most directly benefit from the model's ability to process a pair of texts?
BERT Input Format for Sentence Pairs
Choosing Input Formats for Language Tasks
A language model is being used for four different tasks. Three of these tasks are best addressed by providing the model with a pair of texts to analyze their relationship. One task, however, only requires a single text input. Which task is the outlier that would be handled using a single text input?
Evaluating Language Model Design