hyperparameters to control how to handle long documents

It's common that one might want to use setfit for classifying documents that are longer than max_token_len.

There are several strategies for handling long documents, and the efficacy of each is data dependent:
* Break the document up at max_token_length, possibly avoiding breaking word boundaries.
* Optionally using a sliding window.
* Keeping all the windows, or the first k-windows, or something fancier like finding the most "interesting" windows with respect to the overall corpus.

Then after embedding each window, different classification strategies are possible:
* maxpool then predict
* average then predict
* predict then average

It would be great if these could approaches could be hyperparameters for validation + test.

For train, it might be easiest to insist the training max_token_len is in bounds, alternately the above strategies could be used too.

Related:
https://github.com/UKPLab/sentence-transformers/issues/1673
https://github.com/UKPLab/sentence-transformers/issues/1333
https://github.com/UKPLab/sentence-transformers/issues/1166