I think it depends on your use case and what the inputs represent.
A 2D input using indices (as is used in my example) could represent e.g. a temporal signal, where each time step is assigned to an index. This approach could be used e.g. if you are mapping words to indices and are trying to pass “sequences of words” (i.e. sentences) to the model.
I’m not familiar with your use case and thus also don’t know what the expected predictions are, e.g. a per-word or sentence classification etc.
In case you are trying to reproduce a specific approach explained in a paper, I would assume the authors might have explained their approach there.