--- language: - en - fr - ro - de datasets: - c4 tags: - summarization - translation - openvino license: apache-2.0 --- ## [t5-small](https://huggingface.co/t5-small) exported to the OpenVINO IR. ## Model description [T5](https://huggingface.co/docs/transformers/model_doc/t5#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](https://arxiv.org/pdf/1910.10683.pdf) 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*. ```python 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) ```