Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use ecwk/starencoder-vulnfix-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ecwk/starencoder-vulnfix-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ecwk/starencoder-vulnfix-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ecwk/starencoder-vulnfix-classification") model = AutoModelForSequenceClassification.from_pretrained("ecwk/starencoder-vulnfix-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 383 Bytes
ce80dfa d62fe27 0982e5b d62fe27 ce80dfa | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"epoch": 3.0,
"eval_accuracy": 0.9086826347305389,
"eval_f1": 0.9304446978335233,
"eval_loss": 0.22467140853405,
"eval_precision": 0.9400921658986175,
"eval_recall": 0.9209932279909706,
"eval_roc_auc": 0.9027188362177077,
"eval_runtime": 1.0843,
"eval_samples": 1336,
"eval_samples_per_second": 1232.185,
"eval_steps_per_second": 5.534
} |