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setfit-italian-hate-speech is trained on HaSpeeDe-FB dataset.python -m pip install setfit1from setfit import SetFitModel
2
3# Download from Hub and run inference
4model = SetFitModel.from_pretrained("nickprock/setfit-italian-hate-speech")
5# Run inference
6preds = model(["Lei è una brutta bugiarda!", "Mi piace la pizza"])1@article{https://doi.org/10.48550/arxiv.2209.11055,
2doi = {10.48550/ARXIV.2209.11055},
3url = {https://arxiv.org/abs/2209.11055},
4author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
5keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
6title = {Efficient Few-Shot Learning Without Prompts},
7publisher = {arXiv},
8year = {2022},
9copyright = {Creative Commons Attribution 4.0 International}
10}1@inproceedings{VignaCDPT17,
2 title = {Hate Me, Hate Me Not: Hate Speech Detection on Facebook},
3 author = {Fabio Del Vigna and Andrea Cimino and Felice dell'Orletta and Marinella Petrocchi and Maurizio Tesconi},
4 year = {2017},
5 url = {http://ceur-ws.org/Vol-1816/paper-09.pdf},
6 researchr = {https://researchr.org/publication/VignaCDPT17},
7 cites = {0},
8 citedby = {0},
9 pages = {86-95},
10 booktitle = {Proceedings of the First Italian Conference on Cybersecurity (ITASEC17), Venice, Italy, January 17-20, 2017},
11 editor = {Alessandro Armando and Roberto Baldoni and Riccardo Focardi},
12 volume = {1816},
13 series = {CEUR Workshop Proceedings},
14 publisher = {CEUR-WS.org},
15}