Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use DunnBC22/codebert-base-mlm-Malicious_URLs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/codebert-base-mlm-Malicious_URLs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DunnBC22/codebert-base-mlm-Malicious_URLs")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DunnBC22/codebert-base-mlm-Malicious_URLs") model = AutoModelForSequenceClassification.from_pretrained("DunnBC22/codebert-base-mlm-Malicious_URLs") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 2.0, | |
| "total_flos": 6.728145843607406e+16, | |
| "train_loss": 0.7582937260732105, | |
| "train_runtime": 12885.6962, | |
| "train_samples_per_second": 65.589, | |
| "train_steps_per_second": 2.05 | |
| } |