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:
- fa4e32cab91053903bbf1713255eb1fbf258947fbbba0f9327e75e502e2ed667
- Size of remote file:
- 1.11 GB
- SHA256:
- 849c866b693130db273fcfac940001c2f66c2f3f6ea7a7daabef303b161b5e52
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