README.md

---
license: afl-3.0
language:
- pt
pipeline_tag: text2text-generation
---
# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->
This model is intended to be used generating questions and answers from brazilian portuguese text passages, 
so you can finetune another BERT model into your generated triples (context-question-answer) for extractive question answering without supervision or labeled data.

It was trained using [unicamp-dl/ptt5-base-t5-portuguese-vocab](https://huggingface.co/unicamp-dl/ptt5-base-t5-portuguese-vocab) base model and [Squad 1.1 portuguese version](https://huggingface.co/datasets/ArthurBaia/squad_v1_pt_br) dataset to generante question and answers from text passages.

### Model Description

<!-- Provide a longer summary of what this model is. -->



- **Developed by:** Vitor Alcantara Batista ([email protected])
- **Model type:** T5 base
- **Language(s) (NLP):** Brazilian Portuguese
- **License:** [Academic Free License v. 3.0](https://opensource.org/license/afl-3-0-php/)
- **Finetuned from model :** unicamp-dl/ptt5-base-t5-vocab

### Model Sources [optional]

<!-- Provide the basic links for the model. -->
  
- **Repository:** This model used code from this github repo [https://github.com/patil-suraj/question_generation/](https://github.com/patil-suraj/question_generation/)

## Usage

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->

How to use it (after cloning the github repo above):

```
from pipelines import pipeline
nlp = pipeline("multitask-qa-qg", model='vabatista/question-generation-t5-pt-br', tokenizer='vabatista/question-generation-t5-pt-br')

text = """ PUT YOUR TEXT PASSAGE HERE """
nlp(text) 

```
Sample usage/results:

![sample_results.png](sample_results.png)

## Training Details

TODO

## Model Card Authors

Vitor Alcantara Batista

## Model Card Contact

[email protected]