Toxic Spans Prediction
Project description
MUDES - {Mu}ltilingual {De}tection of Offensive {S}pans
We provide state-of-the-art models to detect toxic spans in text. We have evaluated our models on Toxic Spans task at SemEval 2021 (Task 5).
Installation
You first need to install PyTorch. The recommended PyTorch version is 1.6. Please refer to PyTorch installation page regarding the specific install command for your platform.
When PyTorch has been installed, you can install MUDES from pip.
From pip
pip install mudes
Pretrained MUDES Models
We will be keep releasing new models. Please keep in touch. We have evaluated the models on the trial set released for Toxic Spanstask at SemEval 2021.
Models | Average F1 |
---|---|
en-base | 0.6734 |
en-large | 0.6886 |
multilingual-base | 0.5953 |
multilingual-large | 0.6013 |
Prediction
Following code can be used to predict toxic spans in text. Upon executing, it will download the relevant model and return the toxic spans.
from mudes.app.mudes_app import MUDESApp
app = MUDESApp("en-large", use_cuda=False)
print(app.predict_toxic_spans("You motherfucking cunt", spans=True))
System Demonstration
An experimental demonstration interface called MUDES-UI has been released on GitHub and can be checked out in here.
Citing & Authors
If you are using this repo, please consider citing these papers.
@inproceedings{ranasinghemudes,
title={{MUDES: Multilingual Detection of Offensive Spans}},
author={Tharindu Ranasinghe and Marcos Zampieri},
booktitle={Proceedings of NAACL},
year={2021}
}
@inproceedings{ranasinghe2021semeval,
title={{WLV-RIT at SemEval-2021 Task 5: A Neural Transformer Framework for Detecting Toxic Spans}},
author = "Ranasinghe, Tharindu and Sarkar, Diptanu and Zampieri, Marcos and Ororbia, Alex",
booktitle={Proceedings of SemEval},
year={2021}
}
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