Instructions to use textdetox/bert-multilingual-toxicity-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textdetox/bert-multilingual-toxicity-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textdetox/bert-multilingual-toxicity-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textdetox/bert-multilingual-toxicity-classifier") model = AutoModelForSequenceClassification.from_pretrained("textdetox/bert-multilingual-toxicity-classifier") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ca6f14de014bbd1d5ed4e9e46e6c0fcf255ac910aa997a82bdd065f35bdbb85
- Size of remote file:
- 5.37 kB
- SHA256:
- 13f45e1631cd3dd1a5f0e53516e815f1d3465687f77c62254f0f52a2dd71c017
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