Instructions to use Hate-speech-CNERG/dehatebert-mono-english with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hate-speech-CNERG/dehatebert-mono-english with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hate-speech-CNERG/dehatebert-mono-english")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Hate-speech-CNERG/dehatebert-mono-english") model = AutoModelForSequenceClassification.from_pretrained("Hate-speech-CNERG/dehatebert-mono-english", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 780dbef633f74d692d648fbc721f710713165ab3e715a6862097addaa8a1329b
- Size of remote file:
- 669 MB
- SHA256:
- ce02a5f74e55cff488c487f52773af12f908bbefd0a9267fc19c16906bdc0dd3
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