Instructions to use Cameron/BERT-jigsaw-identityhate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cameron/BERT-jigsaw-identityhate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cameron/BERT-jigsaw-identityhate")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cameron/BERT-jigsaw-identityhate") model = AutoModelForSequenceClassification.from_pretrained("Cameron/BERT-jigsaw-identityhate") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ab4f72a28b1eb04e8a28d8b4359746cfafc169132d3b7ccfe91153fe1e15331
- Size of remote file:
- 433 MB
- SHA256:
- e9ec5249049988573179427c7cb5c7b040d04577b272ea74d390a10e9be4dc73
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