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mudes/en-base
en-base is a token classification model from mudes. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.
We provide state-of-the-art models to detect toxic spans in social media texts. We introduce our framework in this paper. We have evaluated our models on Toxic Spans task at SemEval 2021 (Task 5). Our participation in…
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From the Hugging Face model README
We provide state-of-the-art models to detect toxic spans in social media texts. We introduce our framework in this paper. We have evaluated our models on Toxic Spans task at SemEval 2021 (Task 5). Our participation in the task is detailed in this paper.
You can use this model when you have MUDES installed:
pip install mudes
Then you can use the model like this:
from mudes.app.mudes_app import MUDESApp
app = MUDESApp("en-base", use_cuda=False)
print(app.predict_toxic_spans("You motherfucking cunt", spans=True))
An experimental demonstration interface called MUDES-UI has been released on GitHub and can be checked out in here.
If you find this model helpful, feel free to cite our publications
@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}
}