In this episode of The Prompt Desk podcast, hosts Bradley Arsenault and Justin Macorin dive deep into the world of fine-tuning large language models. They discuss:
The evolution of data preparation techniques from traditional NLP to modern LLMs
Strategies for creating high-quality datasets for fine-tuning
The surprising effectiveness of small, well-curated datasets
Best practices for aligning training data with production environments
The importance of data quality and its impact on model performance
Practical tips for engineers working on LLM fine-tuning projects
Whether you're a seasoned AI practitioner or just getting started with large language models, this episode offers valuable insights into the critical process of data preparation and fine-tuning. Join Brad and Justin as they share their expertise and help you navigate the challenges of building effective AI systems.---Continue listening to The Prompt Desk Podcast for everything LLM & GPT, Prompt Engineering, Generative AI, and LLM Security.Check out PromptDesk.ai for an open-source prompt management tool.Check out Brad’s AI Consultancy at bradleyarsenault.meAdd Justin Macorin and Bradley Arsenault on LinkedIn.
Podden och tillhörande omslagsbild på den här sidan tillhör Justin Macorin, Bradley Arsenault. Innehållet i podden är skapat av Justin Macorin, Bradley Arsenault och inte av, eller tillsammans med, Poddtoppen.
