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:
- 752b69b406201a6d211557d1ee07c100bd3f0f21a74fed28a5a16c2cfbe1d2b4
- Size of remote file:
- 670 MB
- SHA256:
- 47f7adce6f1843d3721b5c896daaed655fadde2dbf933265b861218c067e3a38
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