Instructions to use neuralsentry/vulnfixClassification-StarEncoder-DCMB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neuralsentry/vulnfixClassification-StarEncoder-DCMB with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="neuralsentry/vulnfixClassification-StarEncoder-DCMB")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("neuralsentry/vulnfixClassification-StarEncoder-DCMB") model = AutoModelForSequenceClassification.from_pretrained("neuralsentry/vulnfixClassification-StarEncoder-DCMB", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 383 Bytes
56e83bc | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"epoch": 10.0,
"eval_accuracy": 0.9769967138162595,
"eval_f1": 0.9777347531461762,
"eval_loss": 0.17970030009746552,
"eval_precision": 0.98413140311804,
"eval_recall": 0.9714207199780159,
"eval_roc_auc": 0.977228217131865,
"eval_runtime": 7.2505,
"eval_samples": 6999,
"eval_samples_per_second": 965.318,
"eval_steps_per_second": 7.586
} |