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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c8ee77342645e99e42daf28c86f7e11710751d8b3f7da2c4b47cfbdb68423138
- Size of remote file:
- 711 MB
- SHA256:
- f83ff133690ade7432a57c34d49b3bd2d0c35e6475d38029c047f3dc9fd9de77
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