Examples/guidance for BERT with "sentence" pairs

I’m interested in using a BERT model to classify pairs of text sequences–specifically the titles or abstracts of scientific papers. I’ve been working mostly from https://github.com/allenai/scibert so far, which only seems to have examples of classification using the [CLS] token (https://github.com/allenai/scibert/blob/master/scibert/models/bert_text_classifier.py#L76). Specifically, is there a way to signal the segment difference to the BERT tokenizer? Unlike the [CLS] token, the [SEP] token isn’t guaranteed to be in a specific index position. Is there a way programmatically find this?

Also, note that I’m using the same alternate AllenNLP branch as SciBERT, which may complicate things a bit. If anybody has advice pertaining to just the main AllenNLP branch, I’m happy (ok, well not delighted, but willing) to try sorting out whatever differences there are.

Arman pointed me to the following, which seems to answer my questions well: https://github.com/allenai/sequential_sentence_classification