MLOps Foundations: Working with the Hugging Face Hub CLI

As machine learning models grow in size and complexity, managing your assets efficiently becomes a core engineering challenge. The Hugging Face Hub CLI provides a powerful, scriptable way to version, download, and share models and datasets without leaving your terminal. This text-based course guides you through the essentials of using the Hugging Face Hub Command Line Interface. You will gain the confidence to integrate Hub operations into your automated MLOps pipelines, manage large files securely, and collaborate effectively on machine learning projects. What you'll learn: Understand foundational MLOps concepts and the role of the Hugging Face Hub; Configure secure authentication tokens and manage user sessions via the CLI; Download and upload models, datasets, and space repositories programmatically; Version your machine learning assets using Git-based workflows and Git LFS; Integrate CLI commands into automated scripts and basic CI/CD pipelines; Practice safe asset management through caching control and storage optimization. The course begins with essential definitions of MLOps and Hugging Face ecosystem basics, then moves step-by-step through configuration, file transfers, versioning, and automation practices. You will learn through clear, written explanations and structured command-line examples. This course is designed for beginner machine learning engineers, data scientists, and developers looking to streamline their model deployment workflows. No prior experience with Hugging Face is required, though basic familiarity with the command line is helpful. Start managing your machine learning workflows like a professional today.