T5 is an encoder-decoder model pre-trained on a multi-task mixture of unsupervised and supervised tasks and for which each task is converted into a text-to-text format.
For more information, please take a look at the original paper.
Authors: Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu
You can use this model with Transformers pipeline.
from transformers import AutoTokenizer, pipeline from optimum.onnxruntime import ORTModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("echarlaix/t5-small-dynamic") model = ORTModelForSeq2SeqLM.from_pretrained("echarlaix/t5-small-dynamic") translator = pipeline("translation_en_to_fr", model=model, tokenizer=tokenizer) text = "He never went out without a book under his arm, and he often came back with two." results = translator(text) print(results)
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