Fine-Tuning Language Models with Declarative ML Orchestration

Discover how to fine-tune Language Models (LMs) using declarative ML orchestration in this comprehensive workshop from the Toronto Machine Learning Series. Learn about the widespread use of LMs, their evolution into Large Language Models (LLMs), and their role as foundation models. Explore the challenges of fine-tuning these models, particularly in terms of infrastructure and compute resources. Gain hands-on experience using Flyte to declaratively specify infrastructure for configuring training jobs on required compute resources. Master the process of fine-tuning LMs on proprietary data, overcoming barriers such as runtime environment setup. Benefit from the expertise of Niels Bantilan, Chief Machine Learning Engineer at Union.ai, as he guides you through this 1 hour and 31 minute session, equipping you with practical skills to leverage LMs for specific use cases.