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README.md
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---
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license: afl-3.0
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language:
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- pt
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pipeline_tag: text2text-generation
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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This model is intended to be used generating questions and answers from brazilian portuguese text passages,
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so you can finetune another BERT model into your generated triples (context-question-answer) for extractive question answering without supervision or labeled data.
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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.
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** Vitor Alcantara Batista (vabatista@gmail.com)
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- **Model type:** T5 base
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- **Language(s) (NLP):** Brazilian Portuguese
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- **License:** [Academic Free License v. 3.0](https://opensource.org/license/afl-3-0-php/)
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- **Finetuned from model :** unicamp-dl/ptt5-base-t5-vocab
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** This model used code from this github repo [https://github.com/patil-suraj/question_generation/](https://github.com/patil-suraj/question_generation/)
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## Usage
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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How to use it (after cloning the github repo above):
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```
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from pipelines import pipeline
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nlp = pipeline("multitask-qa-qg", model='vabatista/question-generation-t5-pt-br', tokenizer='vabatista/question-generation-t5-pt-br')
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text = """ PUT YOUR TEXT PASSAGE HERE """
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nlp(text)
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```
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Sample usage/results:
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![sample_results.png](sample_results.png)
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## Training Details
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TODO
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## Model Card Authors
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Vitor Alcantara Batista
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## Model Card Contact
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vabatista@gmail.com
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