[Model] Add T5 model (2/2)

[NickLucche]

Add support fot T5 (encoder-decoder model).
Follow-up and based on #11334, so it needs this other PR merged before it can be addressed, as it assumes to have a backend that supports passing a custom attention bias in both prefill and decode (xformers+pagedattention as of now).

Some topics I'd like to discuss here:

• xFormers is a hard dependency for T5 as of now, do we silently enforce the backend or just raise an error? Surely we need to raise one on platforms xformers does not support (rocm)
• T5 uses the same decoder_start_token_id as it does for padding, but there's no explicit BOS. Current logic in preprocess.py would just crash. Is this the best approach to handle the quirk of T5?
• change to xformers.py I'd rather have been able to spare this one, but it was assuming alibi_slopes were the only way to have multiple attention biases (one per sequence).

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[NickLucche]

we can drop this folder altogether, ../language/language was never really great