metadata

license: mit
language:
  - pt

bertimbau-large-ner-total

This model card aims to simplify the use of the portuguese Bert, a.k.a, Bertimbau for the Named Entity Recognition task.

For this model card the we used the BERT-CRF (total scenario, 10 classes) model available in the ner_evaluation folder of the original Bertimbau repo.

Available classes are:

PESSOA
ORGANIZACAO
LOCAL
TEMPO
VALOR
ABSTRACCAO
ACONTECIMENTO
COISA
OBRA
OUTRO

Usage

# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification

tokenizer = AutoTokenizer.from_pretrained("marquesafonso/bertimbau-large-ner-total")
model = AutoModelForTokenClassification.from_pretrained("marquesafonso/bertimbau-large-ner-total")

Example

from transformers import pipeline

pipe = pipeline("ner", model="marquesafonso/bertimbau-large-ner-total", aggregation_strategy='simple')

sentence = "James Marsh, realizador de filmes como A Teoria de Tudo ou Homem no Arame, assumiu a missão de criar uma obra biográfica sobre Samue Beckett, figura ímpar da literatura e da dramaturgia do século XX. O guião foi escrito pelo escocês Neil Forsyth, vencedor de dois Baftas."

result = pipe([sentence])

print(f"{sentence}\n{result}")

Acknowledgements

This work is an adaptation of portuguese Bert, a.k.a, Bertimbau. You may check and/or cite their work:

@InProceedings{souza2020bertimbau,
    author="Souza, F{\'a}bio and Nogueira, Rodrigo and Lotufo, Roberto",
    editor="Cerri, Ricardo and Prati, Ronaldo C.",
    title="BERTimbau: Pretrained BERT Models for Brazilian Portuguese",
    booktitle="Intelligent Systems",
    year="2020",
    publisher="Springer International Publishing",
    address="Cham",
    pages="403--417",
    isbn="978-3-030-61377-8"
}


@article{souza2019portuguese,
    title={Portuguese Named Entity Recognition using BERT-CRF},
    author={Souza, F{\'a}bio and Nogueira, Rodrigo and Lotufo, Roberto},
    journal={arXiv preprint arXiv:1909.10649},
    url={http://arxiv.org/abs/1909.10649},
    year={2019}
}

Note that the authors - Fabio Capuano de Souza, Rodrigo Nogueira, Roberto de Alencar Lotufo - have used an MIT LICENSE for their work.