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"id2label": {
"0": "non-sensitive",
"1": "sensitive"
}1from transformers import pipeline
2
3pipe = pipeline(model='cardiffnlp/twitter-roberta-base-sensitive-binary')
4text = "Call me today to earn some money mofos!"
5
6pipe(text)[{'label': 'sensitive', 'score': 0.999821126461029}]@article{antypas2024sensitive,
title={Sensitive Content Classification in Social Media: A Holistic Resource and Evaluation},
author={Antypas, Dimosthenis and Sen, Indira and Perez-Almendros, Carla and Camacho-Collados, Jose and Barbieri, Francesco},
journal={arXiv preprint arXiv:2411.19832},
year={2024}
}