The availability of curated collections of models is essential for the application of techniques like Machine Learning (ML) and Data Analytics to MDE as well as to boost research activities.

However, many applications of ML to address MDE tasks are currently limited to small datasets. In this demo we will present ModelSet, a dataset composed of 5,000 Ecore models and 5,000 UML models which has been manually labelled to support Machine Learning tasks (http://modelset.github.io). ModelSet is built upon the models collected by the MAR search engine (http://mar-search.org), which provides more than 500,000 models of different types. We will describe the structure of the dataset and we will explain how to use the associated library to develop ML applications in Python. Finally, we will describe some applications which can be addressed using ModelSet.