This is frequently a topic here on HN. E.g.:

https://udlbook.github.io/udlbook/ (https://news.ycombinator.com/item?id=38424939)

https://fleuret.org/francois/lbdl.html (https://news.ycombinator.com/item?id=35767789)

https://www.fast.ai/ (https://news.ycombinator.com/item?id=24237207)

https://d2l.ai/ (https://news.ycombinator.com/item?id=38428225)

Some more:

https://news.ycombinator.com/item?id=35543774

There is a lot more. Just google for "deep learning", and you'll find a lot of content. And most of that will cover attention, as it is a really basic concept now.

Thanks for the udl book (Understanding Deep Learning), that looks like a really great starting point.

To add to the excellent resources that have already been posted, Chapter 9 of Jurafsky and Martin's "Speech and Language Processing" has a nice overview of attention, and the next chapter talks specifically about the Transformer architecture: https://web.stanford.edu/~jurafsky/slp3/

I doubt any.