Instructions to use dar1bi/bert-phishing-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dar1bi/bert-phishing-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dar1bi/bert-phishing-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dar1bi/bert-phishing-classifier") model = AutoModelForSequenceClassification.from_pretrained("dar1bi/bert-phishing-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7422b0d9ec988788326a154f5b1b887012d33db2f1cc21dd7f6d904cae1d16a8
- Size of remote file:
- 5.27 kB
- SHA256:
- 7d818fc3891c68f380d58910c32e8a594d902cd6997ea18c907d10f68159b7d9
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