Add usage example

README.md

@@ -1,3 +1,46 @@
 ---
+language:
+- en
+- fr
+- ro
+- de
+datasets:
+- c4
+tags:
+- summarization
+- translation
+
 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)
+```