Learn Before
Standard Language Modeling
Standard Language Modeling is a pre-training objective that trains a model to optimize the probability of a text sequence, , from a given corpus. This is typically achieved through an auto-regressive generation procedure where the model predicts each subsequent token based on its preceding context.
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References
Open Prompt(Reference)
Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
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
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
Data Science
Ch.1 Pre-training - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Ch.2 Generative Models - Foundations of Large Language Models
Learn After
A language model is being trained with the objective of predicting the next item in a sequence, given all the preceding items. If this model is processing the sentence 'The cat sat on the mat.', which of the following scenarios accurately represents a single step in its training process?
Choosing a Pre-training Objective for Text Generation
Limitations of a Unidirectional Pre-training Objective