Instructions to use tomh/toxigen_hatebert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tomh/toxigen_hatebert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tomh/toxigen_hatebert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tomh/toxigen_hatebert") model = AutoModelForSequenceClassification.from_pretrained("tomh/toxigen_hatebert") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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```bibtex
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@inproceedings{hartvigsen2022toxigen,
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title = "{T}oxi{G}en:
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author = "Hartvigsen, Thomas and Gabriel, Saadia and Palangi, Hamid and Sap, Maarten and Ray, Dipankar and Kamar, Ece",
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booktitle = "Proceedings of the 60th Annual Meeting of the Association of Computational Linguistics",
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year = "2022"
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```bibtex
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@inproceedings{hartvigsen2022toxigen,
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title = "{T}oxi{G}en: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection",
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author = "Hartvigsen, Thomas and Gabriel, Saadia and Palangi, Hamid and Sap, Maarten and Ray, Dipankar and Kamar, Ece",
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booktitle = "Proceedings of the 60th Annual Meeting of the Association of Computational Linguistics",
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year = "2022"
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