Guide to Large Language Models

This post introduces Large Language Models (LLMs) as a specific type of machine learning model. It elaborates on their capabilities, historical context, and practical applications across various domains like content generation, summarization, and code assistance. Key techniques for leveraging LLMs are detailed, including fine-tuning, RLHF, and prompt engineering, with an emphasis on adapting base models to proprietary data for specialized business use cases. The post also touches upon the challenges of LLM adoption and provides industry-specific examples.