Instructions to use BenjaminOcampo/model-hatebert__trained-in-toxigen__seed-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BenjaminOcampo/model-hatebert__trained-in-toxigen__seed-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BenjaminOcampo/model-hatebert__trained-in-toxigen__seed-1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/model-hatebert__trained-in-toxigen__seed-1") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/model-hatebert__trained-in-toxigen__seed-1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e91d92447cdd19959843da7545da00e55f3c952f41dc9cbc8911cd774262a69
- Size of remote file:
- 438 MB
- SHA256:
- 201e8c0a7b9b3be9060d9bd5ae9574ea61c9b22003bf4b6c1ce91165388032a4
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