AraGPT2 Detector

Machine generated detector model from the AraGPT2: Pre-Trained Transformer for Arabic Language Generation paper

This model is trained on the long text passages, and achieves a 99.4% F1-Score.

How to use it:

from transformers import pipeline
from arabert.preprocess import ArabertPreprocessor

processor = ArabertPreprocessor(model="aubmindlab/araelectra-base-discriminator")
pipe = pipeline("sentiment-analysis", model = "aubmindlab/aragpt2-mega-detector-long")

text = " "
text_prep = processor.preprocess(text)
result = pipe(text_prep)
# [{'label': 'machine-generated', 'score': 0.9977743625640869}]

If you used this model please cite us as :

@misc{antoun2020aragpt2,
      title={AraGPT2: Pre-Trained Transformer for Arabic Language Generation},
      author={Wissam Antoun and Fady Baly and Hazem Hajj},
      year={2020},
      eprint={2012.15520},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

Contacts

Wissam Antoun : Linkedin | Twitter | Github | wfa07@mail.aub.edu | wissam.antoun@gmail.com

Fady Baly : Linkedin | Twitter | Github | fgb06@mail.aub.edu | baly.fady@gmail.com