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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a733e091ce0aeeac769a68623ac49ecf5dab32c3143a82f34ba5c9700074351
- Size of remote file:
- 1.42 GB
- SHA256:
- 8345d1b8f7fd9043ba83adf40cd2f08556d3b3296fa92114aea96f29a779c45e
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