The article provides an overview of utilizing the Comet REST API for managing and downloading machine learning models, focusing on its application in experiment tracking and model registry. It explains how to set up a connection to the Comet REST API by configuring the HTTP Authorization Header with a Comet API key and demonstrates how to access various Comet objects such as workspaces, projects, experiments, and models using specific URL parameters. The integration of Comet's REST API with scripting, particularly through curl commands, is highlighted as a method for automating the download of models from the Comet Model Registry. Additionally, the article touches upon the potential of Comet's tools in supporting real-time model tuning and their compatibility with CI/CD pipelines, emphasizing the convenience of maintaining the most recent and effective models for production applications.