t5-small exported to the OpenVINO IR.
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.intel.openvino import OVModelForSeq2SeqLM
model_id = "echarlaix/t5-small-openvino"
model = OVModelForSeq2SeqLM.from_pretrained(model_id, use_cache=False)
tokenizer = AutoTokenizer.from_pretrained(model_id)
# Create a pipeline
translation_pipe = 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."
result = translation_pipe(text)