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# Introduction

The _learnware_ paradigm was proposed by Professor Zhi-Hua Zhou in 2016 [1, 2]. In this 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.
_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.

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.



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# 简介

学件范式由周志华教授在 2016 年提出 [1, 2]。在学件范式下,世界各地的开发者可分享模型至学件基座系统,系统通过有效查搜和复用学件帮助用户高效解决机器学习任务,而无需从零开始构建机器学习模型。
学件由周志华教授在 2016 年提出 [1, 2]。在学件范式下,世界各地的开发者可分享模型至学件基座系统,系统通过有效查搜和复用学件帮助用户高效解决机器学习任务,而无需从零开始构建机器学习模型。

本项目开发的 `learnware` 包对学件范式中的核心组件和算法进行了实现,全流程地支持学件上传、检测、组织、查搜、部署和复用等功能。基于良好的结构设计,`learnware` 包具有高度可扩展性,为后续相关算法和功能的开发打下坚实基础。



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