The >10 fingers problem should be solved via higher quality data or conditioning rather than a better model architecture.
I don't understand how neutral networks operate, but my layman's guess is that when you sometimes see hands with 5 fingers visible, sometimes 4, sometimes 3, sometimes 2, sometimes 1, and sometimes 0, then it's not immediately apparent that it means that every hand has between 5 and 0 fingers.
Think of it this way, if the AI has ever only seen houses with a maximum of 10 windows in it's entire training set, is it so unthinkable that it sometimes draws a house with 12 windows? that's a "sensible" understanding about how houses have a variable amount of windows. It just doesn't work for fingers.
I'm sure the same issue would arise if humans had other body parts that came in large quantities, but almost everything else is either 1 or 2 like the nose or eyes.
But I think what the grant parent means by conditioning is non-textual conditioning, like ControlNet. This will always be more powerful than trying to describe something by text. Think about the description of a character in a novel vs the movie adaptation.
you do not draw an individual with anomalous hands because you have an ontological model in which "humans normally have five fingers per hand".
Knowing "how the world works" is the appropriate source for subsequent expression of a representation.
Somewhere in the architecture a world model should be formed.