Creating Instruction Datasets for LLM Fine-tuning - A Beginner's Guide

Learn essential strategies for creating instruction datasets and fine-tuning Large Language Models (LLMs) in this comprehensive 25-minute tutorial that addresses common questions from beginners and non-coders. Explore when and how to fine-tune LLMs, methods for converting pure text files into instruction datasets, and techniques for domain-specific training. Discover the differences between general domain knowledge fine-tuning and instruction-based datasets, understand multi-task fine-tuning approaches, and evaluate various AutoML tools for no-code implementation. Gain insights into synthetic datasets like Open ORCA, learn how to leverage AI assistants like Bard and GPT-4 for fine-tuning advice, and understand the fundamental concepts of instruction tuning methodology. Drawing from recent research, including the August 2023 survey on instruction tuning approaches, examine how LLMs bridge the gap between next-word prediction and human instruction adherence through training on instruction-output pairs.