|
--- |
|
license: mit |
|
--- |
|
# bertimbau-large-ner |
|
|
|
This model card aims to simplify the use of the [portuguese Bert, a.k.a, Bertimbau](https://github.com/neuralmind-ai/portuguese-bert) for the Named Entity Recognition task. |
|
|
|
For this model card the we used the BERT-CRF (selective scenario, 5 classes) model available in the [ner_evalutaion](https://github.com/neuralmind-ai/portuguese-bert/tree/master/ner_evaluation) folder of the original Bertimbau repo. |
|
|
|
## Usage |
|
|
|
``` |
|
# Load model directly |
|
from transformers import AutoTokenizer, AutoModelForTokenClassification |
|
|
|
tokenizer = AutoTokenizer.from_pretrained("marquesafonso/bertimbau-large-ner") |
|
model = AutoModelForTokenClassification.from_pretrained("marquesafonso/bertimbau-large-ner") |
|
|
|
``` |
|
|
|
## Example |
|
|
|
``` |
|
from transformers import pipeline |
|
|
|
pipe = pipeline("token-classification", model="marquesafonso/bertimbau-large-ner") |
|
|
|
sentence = "Acima de Ederson, abaixo de Rúben Dias. É entre os dois jogadores do Manchester City que se vai colocar Gonçalo Ramos no ranking de vendas mais avultadas do Benfica." |
|
|
|
result = pipe([sentence]) |
|
|
|
print(f"{sentence}\n{result}") |
|
|
|
# Acima de Ederson, abaixo de Rúben Dias. É entre os dois jogadores do Manchester City que se vai colocar Gonçalo Ramos no ranking de vendas mais avultadas do Benfica. |
|
# [[{'entity': 'B-PESSOA', 'score': 0.99976975, 'index': 4, 'word': 'Ed', 'start': 9, 'end': 11}, {'entity': 'I-PESSOA', 'score': 0.9941182, 'index': 5, 'word': '##erson', 'start': 11, 'end': 16}, {'entity': 'B-PESSOA', 'score': 0.9998306, 'index': 9, 'word': 'R', 'start': 28, 'end': 29}, {'entity': 'I-PESSOA', 'score': 0.9737293, 'index': 10, 'word': '##ú', 'start': 29, 'end': 30}, {'entity': 'I-PESSOA', 'score': 0.9944133, 'index': 11, 'word': '##ben', 'start': 30, 'end': 33}, {'entity': 'I-PESSOA', 'score': 0.9994117, 'index': 12, 'word': 'Dias', 'start': 34, 'end': 38}, {'entity': 'B-ORGANIZACAO', 'score': 0.94043595, 'index': 20, 'word': 'Manchester', 'start': 69, 'end': 79}, {'entity': 'I-ORGANIZACAO', 'score': 0.9870952, 'index': 21, 'word': 'City', 'start': 80, 'end': 84}, {'entity': 'B-PESSOA', 'score': 0.9997652, 'index': 26, 'word': 'Gonçalo', 'start': 104, 'end': 111}, {'entity': 'I-PESSOA', 'score': 0.9989994, 'index': 27, 'word': 'Ramos', 'start': 112, 'end': 117}, {'entity': 'B-ORGANIZACAO', 'score': 0.9033079, 'index': 37, 'word': 'Benfica', 'start': 157, 'end': 164}]] |
|
``` |
|
|
|
## Acknowledgements |
|
|
|
This work is an adaptation of [portuguese Bert, a.k.a, Bertimbau](https://github.com/neuralmind-ai/portuguese-bert). You may check and/or cite their [work](http://arxiv.org/abs/1909.10649): |
|
|
|
``` |
|
@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. |
