英文

setfit-意大利仇恨言论

这是一个可用于文本分类的模型。该模型使用了一种高效的少样本学习技术,包括:

  • 对一个 Sentence Transformer 进行对比学习的微调。
  • 使用来自经过微调的句子转换器的特征进行分类。
  • 此模型用于检测意大利语的仇恨言论:

    • 1 ——> 是仇恨言论
    • 0 ——> 不是仇恨言论

    数据集

    setfit-意大利仇恨言论是使用 HaSpeeDe-FB 数据集进行训练的。

    用法

    要将此模型用于推理,请先安装SetFit库:

    python -m pip install setfit
    

    然后,你可以按以下方式运行推理:

    from setfit import SetFitModel
    
    # Download from Hub and run inference
    model = SetFitModel.from_pretrained("nickprock/setfit-italian-hate-speech")
    # Run inference
    preds = model(["Lei è una brutta bugiarda!", "Mi piace la pizza"])
    

    BibTeX条目和引用信息

    @article{https://doi.org/10.48550/arxiv.2209.11055,
    doi = {10.48550/ARXIV.2209.11055},
    url = {https://arxiv.org/abs/2209.11055},
    author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
    keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
    title = {Efficient Few-Shot Learning Without Prompts},
    publisher = {arXiv},
    year = {2022},
    copyright = {Creative Commons Attribution 4.0 International}
    }
    

    数据集引用

    @inproceedings{VignaCDPT17,
      title = {Hate Me, Hate Me Not: Hate Speech Detection on Facebook},
      author = {Fabio Del Vigna and Andrea Cimino and Felice dell'Orletta and Marinella Petrocchi and Maurizio Tesconi},
      year = {2017},
      url = {http://ceur-ws.org/Vol-1816/paper-09.pdf},
      researchr = {https://researchr.org/publication/VignaCDPT17},
      cites = {0},
      citedby = {0},
      pages = {86-95},
      booktitle = {Proceedings of the First Italian Conference on Cybersecurity (ITASEC17), Venice, Italy, January 17-20, 2017},
      editor = {Alessandro Armando and Roberto Baldoni and Riccardo Focardi},
      volume = {1816},
      series = {CEUR Workshop Proceedings},
      publisher = {CEUR-WS.org},
    }