Instructions to use sonnv/toxic_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sonnv/toxic_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sonnv/toxic_detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sonnv/toxic_detection") model = AutoModelForSequenceClassification.from_pretrained("sonnv/toxic_detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31a663ec97d5f7236cd57d8cf692ac98ed532bcc59566a638ac3a59e62c8a831
- Size of remote file:
- 232 MB
- SHA256:
- 8c078cae414aaecb8f4cda382a247ce3d00ed540f497783c4e2a6f9fa0a13326
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