Instructions to use danielcd99/multilanguage-toxicity-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielcd99/multilanguage-toxicity-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="danielcd99/multilanguage-toxicity-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("danielcd99/multilanguage-toxicity-classifier") model = AutoModelForSequenceClassification.from_pretrained("danielcd99/multilanguage-toxicity-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd1cabdbf809ee74b44a8b2a7c2ab5d04b15a23c17637d7f67fc4cf3e76538d6
- Size of remote file:
- 3.58 kB
- SHA256:
- 7bcef1d2a2886cc33647b250c73ca0869bca3ced405c0c79ac7408a7c50a53b5
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