Instructions to use AnonymousCS/HateBERT_hateval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/HateBERT_hateval with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/HateBERT_hateval")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/HateBERT_hateval") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/HateBERT_hateval", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03659aadfc513124df3d3ed3c9f7a3bd1361cc1c5cdcc0147679224fb2adfb1a
- Size of remote file:
- 438 MB
- SHA256:
- b1d297d280afd9c7c966fb7e78089bcefe452bf4f77de1762d47229c519c7bfd
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