Instructions to use Moaaz2os/stip-threat-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Moaaz2os/stip-threat-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Moaaz2os/stip-threat-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Moaaz2os/stip-threat-classifier") model = AutoModelForSequenceClassification.from_pretrained("Moaaz2os/stip-threat-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 760214be12cdb1d87f9721cbd00fb2b1f2bad099fc366f8cfa4586204bdda16b
- Size of remote file:
- 436 MB
- SHA256:
- 702885c7868f4c19e6adf0b033756fe2c76b5b574343758ce93376b0f2271f1e
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