  New machine learning algorithms are being developed to solve problems in
different areas, including music. Intuitive, accessible, and understandable
demonstrations of the newly built models could help attract the attention of
people from different disciplines and evoke discussions. However, we notice
that it has not been a common practice for researchers working on musical
machine learning to demonstrate their models in an interactive way. To address
this issue, we present in this paper an template that is specifically designed
to demonstrate symbolic musical machine learning models on the web. The
template comes with a small codebase, is open source, and is meant to be easy
to use by any practitioners to implement their own demonstrations. Moreover,
its modular design facilitates the reuse of the musical components and
accelerates the implementation. We use the template to build interactive
demonstrations of four exemplary music generation models. We show that the
built-in interactivity and real-time audio rendering of the browser make the
demonstration easier to understand and to play with. It also helps researchers
to gain insights into different models and to A/B test them.
