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README.md

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+---
+inference: false
+---
+
+
+<!-- ---
+language: pt
+license: mit
+tags:
+- t5
+- pytorch
+- tensorflow
+datasets:
+- brWaC
+widget:
+- text: "Texto de exemplo em português"
+--- -->
+
+<!-- inference: false -->
+
+# Portuguese T5 (aka "PTT5")
+
+## Introduction
+PTT5 is a T5 model pretrained in the BrWac corpus, a large  collection  of  web  pages in Portuguese, improving T5's performance on Portuguese sentence similarity and entailment tasks. It's available in three sizes (small, base and large) and two vocabularies (Google's T5 original and ours, trained on Portuguese Wikipedia).
+
+For further information or requests, please go to [PTT5 repository](https://github.com/unicamp-dl/PTT5).
+
+## Available models
+| Model                                    | Size                                                   | #Params  | Vocabulary         |
+| :-:                                      | :-:                                                            | :-:      | :-:                |
+| [unicamp-dl/ptt5-small-t5-vocab](https://huggingface.co/unicamp-dl/ptt5-small-t5-vocab)                   | small | 60M  | Google's T5 |
+| [unicamp-dl/ptt5-base-t5-vocab](https://huggingface.co/unicamp-dl/ptt5-base-t5-vocab)                     | base  | 220M | Google's T5 |
+| [unicamp-dl/ptt5-large-t5-vocab](https://huggingface.co/unicamp-dl/ptt5-large-t5-vocab)                   | large | 740M | Google's T5 |
+| [unicamp-dl/ptt5-small-portuguese-vocab](https://huggingface.co/unicamp-dl/ptt5-small-portuguese-vocab)   | small | 60M  | Portuguese  |
+| **[unicamp-dl/ptt5-base-portuguese-vocab](https://huggingface.co/unicamp-dl/ptt5-base-portuguese-vocab)** **(Recommended)**     | **base**  | **220M** | **Portuguese**  |
+| [unicamp-dl/ptt5-large-portuguese-vocab](https://huggingface.co/unicamp-dl/ptt5-large-portuguese-vocab)   | large | 740M | Portuguese  |
+
+## Usage
+```python
+# Tokenizer 
+from transformers import AutoTokenizer # or T5Tokenizer
+
+# PyTorch (bare model, baremodel + language modeling head)
+from transformers import T5Model, T5ForConditionalGeneration
+
+# Tensorflow (bare model, baremodel + language modeling head)
+from transformers import TFT5Model, TFT5ForConditionalGeneration
+
+model_name = 'unicamp-dl/ptt5-base-portuguese-vocab'
+
+tokenizer = T5Tokenizer.from_pretrained(model_name)
+
+# PyTorch
+model_pt = T5ForConditionalGeneration.from_pretrained(model_name)
+
+# TensorFlow
+model_tf = TFT5ForConditionalGeneration.from_pretrained(model_name)
+```
+
+
+## Citation
+We are preparing an arXiv submission and soon will provide a citation. For now, if you need to cite use:
+```bibtex
+@misc{ptt5_2020,
+  Author = {Carmo, Diedre and Piau, Marcos and Campiotti, Israel and Nogueira, Rodrigo and Lotufo, Roberto},
+  Title = {PTT5: Pre-training and validating the T5 transformer in Brazilian Portuguese data},
+  Year = {2020},
+  Publisher = {GitHub},
+  Journal = {GitHub repository},
+  Howpublished = {\url{https://github.com/unicamp-dl/PTT5}}
+}
+```