  We introduce IT5, the first family of encoder-decoder transformer models
pretrained specifically on Italian. We document and perform a thorough cleaning
procedure for a large Italian corpus and use it to pretrain four IT5 model
sizes. We then introduce the ItaGen benchmark, which includes a broad range of
natural language understanding and generation tasks for Italian, and use it to
evaluate the performance of IT5 models and multilingual baselines. We find
monolingual IT5 models to provide the best scale-to-performance ratio across
tested models, consistently outperforming their multilingual counterparts and
setting a new state-of-the-art for Italian language generation.
