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protectai/codebert-base-Malicious_URLs-onnx
codebert-base-Malicious_URLs-onnx is a text classification model from protectai. Use it when you need a label for a piece of text. It is set up for transformers.
[!WARNING] THIS PROJECT HAS BEEN ARCHIVED. This project and its associated code on GitHub are no longer under active development or maintained.
Downloads · 30 days
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From the Hugging Face model README
[!WARNING] THIS PROJECT HAS BEEN ARCHIVED.
This project and its associated code on GitHub are no longer under active development or maintained.
This model is a conversion of DunnBC22/codebert-base-Malicious_URLs to ONNX format. It's based on the CodeBERT architecture, tailored for the specific task of identifying URLs that may pose security threats. The model was converted to ONNX using the 🤗 Optimum library.
Base Model: CodeBERT-base, a robust model for programming and natural languages.
Dataset: https://www.kaggle.com/datasets/sid321axn/malicious-urls-dataset.
Modifications: Details of any modifications or fine-tuning done to tailor the model for malicious URL detection.
Loading the model requires the 🤗 Optimum library installed.
from optimum.onnxruntime import ORTModelForSequenceClassification
from transformers import AutoTokenizer, pipeline
tokenizer = AutoTokenizer.from_pretrained("laiyer/codebert-base-Malicious_URLs-onnx")
model = ORTModelForSequenceClassification.from_pretrained("laiyer/codebert-base-Malicious_URLs-onnx")
classifier = pipeline(
task="text-classification",
model=model,
tokenizer=tokenizer,
top_k=None,
)
classifier_output = classifier("https://google.com")
print(classifier_output)
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