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
- Xet hash:
- 3010ec59c0bf777b491c4493b8e7446332f97db8b612c2a44ff69070a3e2cb17
- Size of remote file:
- 1.42 GB
- SHA256:
- 99f713523fcc3ac696f210c8f1ffa3cd788b7872d76a6aaf1317133f3ec78d17
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