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# Introduction
<div style="word-break: break-word">
_Learnware_ paradigm was proposed by Professor Zhi-Hua Zhou in 2016 [1, 2]. In the _learnware paradigm_, developers worldwide can share models with the _learnware dock system_, which effectively searches for and reuse learnware(s) to help users solve machine learning tasks efficiently without starting from scratch.
</div >
The `learnware` package provides a fundamental implementation of the central concepts and procedures within the learnware paradigm. Its well-structured design ensures high scalability and facilitates the seamless integration of additional features and techniques in the future.
<div style="word-break: break-word">
The `learnware` package provides a fundamental implementation of the central concepts and procedures within the learnware paradigm. Its well-structured design ensures high scalability and facilitates the seamless integration of additional features and techniques in the future.
</div >
In addition, the `learnware` package serves as the engine for the [Beimingwu System](https://bmwu.cloud) and can be effectively employed for conducting experiments related to learnware.