Instructions to use neuralsentry/vulnerabilityDetection-StarEncoder-Devign with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neuralsentry/vulnerabilityDetection-StarEncoder-Devign with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="neuralsentry/vulnerabilityDetection-StarEncoder-Devign")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("neuralsentry/vulnerabilityDetection-StarEncoder-Devign") model = AutoModelForSequenceClassification.from_pretrained("neuralsentry/vulnerabilityDetection-StarEncoder-Devign", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 386 Bytes
65be213 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"epoch": 10.0,
"eval_accuracy": 0.7019009565322678,
"eval_f1": 0.6654891304347826,
"eval_loss": 0.7599468231201172,
"eval_precision": 0.7660306537378793,
"eval_recall": 0.5882776843622388,
"eval_roc_auc": 0.7028302484311194,
"eval_runtime": 28.5103,
"eval_samples": 8259,
"eval_samples_per_second": 289.685,
"eval_steps_per_second": 6.454
} |