Text Classification
Transformers
Safetensors
English
deberta-v2
phishing-detection
email-security
deberta-v3
Instructions to use takumi123xxx/phishing-email-detector-deberta-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use takumi123xxx/phishing-email-detector-deberta-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="takumi123xxx/phishing-email-detector-deberta-v3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("takumi123xxx/phishing-email-detector-deberta-v3") model = AutoModelForSequenceClassification.from_pretrained("takumi123xxx/phishing-email-detector-deberta-v3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bdffecdcc5b6d42203dc98e75f60761c5f9f2d32f3f54daf33b89b93a806d683
- Size of remote file:
- 1.74 GB
- SHA256:
- 86ac0ada93441640b0477c4c5f03a1128d4550894755c7d490eded8a82944379
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