Text Classification
Transformers
PyTorch
TensorBoard
English
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use DunnBC22/codebert-base-Malicious_URLs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/codebert-base-Malicious_URLs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DunnBC22/codebert-base-Malicious_URLs")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DunnBC22/codebert-base-Malicious_URLs") model = AutoModelForSequenceClassification.from_pretrained("DunnBC22/codebert-base-Malicious_URLs") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b8faf1aa2ddd8d9da7554cd8b022bee91fa214bf5fc7b72c221ec2c33676063
- Size of remote file:
- 499 MB
- SHA256:
- e99bd842102a67cd53368124709d828894c5f7b6310804daa694aea4fa0ae80e
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