Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use dzinampini/phishing-links-detection-using-transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dzinampini/phishing-links-detection-using-transformers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dzinampini/phishing-links-detection-using-transformers")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dzinampini/phishing-links-detection-using-transformers") model = AutoModelForSequenceClassification.from_pretrained("dzinampini/phishing-links-detection-using-transformers") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4301892c53494e2cb6626a1682b9a7c8287c2ecaac1ee4802762b6014aa45ac
- Size of remote file:
- 5.3 kB
- SHA256:
- 1dc15cdd22ce8aecfdfb64d94e8faefb7b398cde9537334ff11543d91669bcc1
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