Practitioners
The Machine Learning Practitioner’s Guide to Fine-Tuning Language Models – MachineLearningMastery.com
In this article, you will learn when fine-tuning large language models is warranted, which 2025-ready methods and tools to choose, and how to avoid the most common mistakes that derail projects. Topics we will cover include: A practical decision framework: prompt engineering, retrieval-augmented generation (RAG), and when fine-tuning truly adds value. Today’s essential methods—LoRA/QLoRA, Spectrum—and…