Building Real-World LLM Products with Fine-Tuning and More with Hamel Husain

This podcast episode from Practical AI features Hamel Husain, founder of Parlance Labs, discussing the practical aspects of building LLM-based products. The conversation covers the journey from initial demos to functional applications, emphasizing the importance of fine-tuning LLMs. It delves into the fine-tuning process, including tools like Axolotl and LoRA adapters, and highlights common evaluation pitfalls. The episode also touches on model optimization, inference frameworks, systematic evaluation techniques, data generation, and the parallels to traditional software engineering. The focus is on providing actionable insights for developers working with LLMs.