Instructions to use dima806/phishing-email-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/phishing-email-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dima806/phishing-email-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dima806/phishing-email-detection") model = AutoModelForSequenceClassification.from_pretrained("dima806/phishing-email-detection") - Inference
- Notebooks
- Google Colab
- Kaggle
Repo
#2
by dreyna001 - opened
Is there a repo somewhere if you're willing to share. If not, are the high level concepts of how you implemented this available. I am working on my own model for an enterprise and I am looking at different courses of action.
dreyna001 changed discussion status to closed
The code is fully available on Kaggle, see the https://www.kaggle.com/dima806/phishing-email-detection-distilbert-huggingface for more details