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:
- 214526408e06c86c57ca8db5fce0b6f5c234d4e3f95e7aed50d5863452b6a9ab
- Size of remote file:
- 3.58 kB
- SHA256:
- 8f8595dc247b23ca631bd65281b4d35f0e46c77dc607a026b5b1e1c720eff85d
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