It's really simple, basically just the magnitude of the value vector, weighted by QK dot product, summed across all attention heads and layers.

When I started, I expected I'd have to experiment a lot to find something comprehensible. But this simple computation can already show some patterns.

Might be cool to try different colors for the different attention heads instead of summing them across all attention heads, and making the backgrounds composed of stacked color layers? So you can see how each attention head attends to tokens individually.

Nice! Sometimes the simplest approaches work the best.

If you want quick access look at google images for "transformer attention formula" there are some interesting depictions