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:
- adb806e028d41d2d4dc703b92edf667b2f52906ffeca4e7386f6bb55c349bc1c
- Size of remote file:
- 499 MB
- SHA256:
- ff57a84452334bf18fdb7bfdff30d887d328cb7f48db63b8bb76b54c8c01768d
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