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") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08298d07f5891cd05e7e793db27d97eef6859c93cea980830e85d7bd5075b3fc
- Size of remote file:
- 438 MB
- SHA256:
- 8464f3a297ee42c52cf2a04f56e236c603989ad7f387ec76aa7bc2b9aa5e150f
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