STM32Cube.AI / scikit-learn in TinyML?

Hello all,

The other day STMicroelectronics announced another update of their IDE, which

"In addition to enabling development of neural networks for edge inference on STM32 microcontrollers (MCUs), the latest STM32Cube.AI release (version 7.0) supports new supervised and semi-supervised methods that work with smaller data sets and fewer CPU cycles. "

Which leads me to this question: have you ever used scikit-learn in a tinyML context? It is possible to convert sklearn models into ONNX, and to use ONNX with STM32Cube.AI, but has it been done yet?

I believe for some applications it could be a pretty good idea, and contrary to pure NNs those “classic” ML models like decision trees or SVMs are usually easily explainable. And scikit-learn has a really friendly API. Has anyone seen anything like that?