t5-small

Model description

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.

Paper: Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Authors: Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu

Usage example

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-onnx")
model = ORTModelForSeq2SeqLM.from_pretrained("echarlaix/t5-small-onnx")
translator = pipeline("translation_en_to_fr", model=model, tokenizer=tokenizer)
results = translator("My name is Eustache and I have a pet raccoon")
print(results)