T5 uses relative scalar embeddings. Encoder input padding can be done on the left and on the right.
See the training, inference and scripts sections below for all details regarding usage.
T5 comes in different sizes:
t5-small
t5-base
t5-large
t5-3b
t5-11b.
Based on the original T5 model, Google has released some follow-up works:
T5v1.1: T5v1.1 is an improved version of T5 with some architectural tweaks, and is pre-trained on C4 only without
  mixing in the supervised tasks. Refer to the documentation of T5v1.1 which can be found here.
mT5: mT5 is a multilingual T5 model. It is pre-trained on the mC4 corpus, which includes 101 languages. Refer to
  the documentation of mT5 which can be found here.
byT5: byT5 is a T5 model pre-trained on byte sequences rather than SentencePiece subword token sequences. Refer
