Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use neuralsentry/vulnfixClassification-DistilBERT-DCMB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neuralsentry/vulnfixClassification-DistilBERT-DCMB with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="neuralsentry/vulnfixClassification-DistilBERT-DCMB")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("neuralsentry/vulnfixClassification-DistilBERT-DCMB") model = AutoModelForSequenceClassification.from_pretrained("neuralsentry/vulnfixClassification-DistilBERT-DCMB", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 386 Bytes
b32141a | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"epoch": 10.0,
"eval_accuracy": 0.9712816116588084,
"eval_f1": 0.9722260605223159,
"eval_loss": 0.1769445687532425,
"eval_precision": 0.9777654252362423,
"eval_recall": 0.9667491068974993,
"eval_roc_auc": 0.9714697915439877,
"eval_runtime": 4.8942,
"eval_samples": 6999,
"eval_samples_per_second": 1430.059,
"eval_steps_per_second": 5.721
} |