Learn how to transform pretrained large language models (LLMs) into effective text classifiers, with a focus on spam classification. The post highlights the process of finetuning GPT models, discussing the modification of model outputs, the importance of transformer blocks, and various experiments to optimize model performance. The release of the author's new book on building GPT-like LLMs from scratch is also announced, providing a deep dive into understanding and constructing LLMs.
Table of contents
Announcing My New BookWhat You’ll Learn in This ArticleDifferent categories of finetuningInitializing a model with pretrained weightsAdding a classification headEvaluating the model performanceInsights from additional experimentsBuild A Large Language Model From ScratchSort: