Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use aisuko/phishing-binary-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aisuko/phishing-binary-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aisuko/phishing-binary-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aisuko/phishing-binary-classification") model = AutoModelForSequenceClassification.from_pretrained("aisuko/phishing-binary-classification") - Notebooks
- Google Colab
- Kaggle
File size: 1,299 Bytes
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},
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"cls_token": "[CLS]",
"do_lower_case": true,
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"max_length": 512,
"model_max_length": 512,
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"stride": 0,
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"tokenize_chinese_chars": true,
"tokenizer_class": "BertTokenizer",
"truncation_side": "right",
"truncation_strategy": "longest_first",
"unk_token": "[UNK]"
}
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