Create README.md

README.md

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+---
+datasets:
+- allenai/c4
+- legacy-datasets/mc4
+language:
+- pt
+pipeline_tag: text2text-generation
+base_model: google-t5/t5-large
+---
+
+# ptt5-v2-large
+
+## Introduction
+[ptt5-v2 models](https://huggingface.co/collections/unicamp-dl/ptt5-v2-666538a650188ba00aa8d2d0) are pretrained T5 models tailored for the Portuguese language, continuing from Google's original checkpoints with sizes from t5-small to t5-3B.
+These checkpoints were used to train MonoT5 rerankers for the Portuguese language, which can be found in their  [HuggingFace collection](https://huggingface.co/collections/unicamp-dl/monoptt5-66653981877df3ea727f720d).
+For further information about the pretraining process, please refer to our paper, [ptt5-v2: A Closer Look at Continued Pretraining of T5 Models for the Portuguese Language](https://arxiv.org/abs/2008.09144).
+
+## Usage
+```python
+from transformers import T5Tokenizer, T5ForConditionalGeneration
+
+tokenizer = T5Tokenizer.from_pretrained("unicamp-dl/ptt5-v2-large")
+model = T5ForConditionalGeneration.from_pretrained("unicamp-dl/ptt5-v2-large")
+```
+
+## Citation
+If you use our models, please cite:
+
+    @article{ptt5_2020,
+      title={PTT5: Pretraining and validating the T5 model on Brazilian Portuguese data},
+      author={Carmo, Diedre and Piau, Marcos and Campiotti, Israel and Nogueira, Rodrigo and Lotufo, Roberto},
+      journal={arXiv preprint arXiv:2008.09144},
+      year={2020}
+    }