It might be fine or whatnot, I’m on mobile and can’t see the file in question. The associated Python code might be a helpful starting point.
In my experience, most models intentionally obfuscate copyright sources. They all know the materials to various degrees, but they are not intended to replicate sources. They all have strong interference in place to obscure both their recognition and reproduction potential. If, for instance, you can identify where errors are inserted and make a few corrections, they often continue adding a few details that are from the original source. If this is done a few times in a row, they tend to gain more freedom before reverting to obfuscation again. This is the behavior I look out for. It is a strong tool too if you get creative in application.
Perhaps someone posts an API to look up the library of congress classification of a work based on a few lines or something. GL