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
File size: 286 Bytes
a4b8910 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"bos_token": "[CLS]",
"cls_token": "[CLS]",
"eos_token": "[SEP]",
"mask_token": "[MASK]",
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"unk_token": {
"content": "[UNK]",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false
}
}
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