The article outlines a quick start guide for using the AX library, focusing on how to efficiently optimize machine learning models. It emphasizes the importance of user feedback, indicating that the team actively incorporates suggestions to improve the tool. This responsiveness suggests a commitment to user experience and continual enhancement of their offerings. Key details include a list of available qualifiers that can be used within the library. Users are directed to the documentation for comprehensive information on these qualifiers, which likely play a significant role in tailoring optimization processes. The guide is designed for users looking to get started quickly, providing essential information without overwhelming them with unnecessary details. Overall, it aims to streamline the initial setup and usage of the AX library for those interested in enhancing their machine learning workflows.