Fine-Tuning of Large Language Models

Large Language Models (LLMs) such as GPT, Claude, and Grok have transformed the landscape of AI, but using them effectively for specific real-world tasks often requires more than prompt engineering. Fine-tuning, task-specific adaptation, and efficient training strategies are essential to unlock their full potential. This workshop is designed for advanced practitioners who want to go beyond using LLMs as generic assistants and learn how to systematically adapt them to rule a particular domain or task. Over the course of 3 hours, participants will gain practical, hands-on experience in training and adapting LLMs. Starting with a pre-trained foundation model, we will walk through the full pipeline of dataset preparation, fine-tuning, evaluation, and deployment. Attendees will bring their laptops and work along, implementing techniques directly in code.