<s>[INST] I'm a data scientist interested in recent machine learning breakthroughs and their applications. I'm specifically concerned with model interpretability. 

Like many, I've been blown away by the performances of attention-based models, but also by their opacity - understanding what's happening under the hood of transformers has proven difficult at best. I'm curious to know more about techniques and tools that help in interpreting attention-based models that are used to process sequential data.

Can you shed some light on this topic?[/INST]