Text Classification
Transformers
Safetensors
English
bert
url
cybersecurity
urls
links
classification
phishing-detection
tiny
phishing
malware
defacement
urlbert
malicious
text-embeddings-inference
Instructions to use CrabInHoney/urlbert-tiny-v3-malicious-url-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CrabInHoney/urlbert-tiny-v3-malicious-url-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CrabInHoney/urlbert-tiny-v3-malicious-url-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CrabInHoney/urlbert-tiny-v3-malicious-url-classifier") model = AutoModelForSequenceClassification.from_pretrained("CrabInHoney/urlbert-tiny-v3-malicious-url-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75536999e338e01eb73b5c34c5bfd8f96307603d466a0e88d2be539467cc04bd
- Size of remote file:
- 14.8 MB
- SHA256:
- 94015d9583bf0ad83308cf5758cbe4c272edd8654afa6c441389bb7688679cd7
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