Learn how to leverage MLflow for tracking and managing the fine-tuning process of Large Language Models (LLMs) in this comprehensive 49-minute video tutorial. Discover techniques for monitoring all activities during LLM fine-tuning, registering models in a model server, and retrieving models from the registry for inference. Gain hands-on experience with practical examples and access the accompanying Jupyter notebook for in-depth understanding of MLOps practices in data science and machine learning workflows.
MLOps with MLflow: Fine-Tuning LLMs - Tracking Experiments and Logging Models
The Machine Learning Engineer via YouTube
Overview
Syllabus
MLOps with Mlflow: Fine Tune LLM Track experiments and Log Models #datascience #machinelearning
Taught by
The Machine Learning Engineer
