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
Download eval_results.json from ecwk/starencoder-vulnfix-classification: direct link, hf CLI and curl.
- Browser
- Download file 383 Bytes
-
https://huggingface.co/ecwk/starencoder-vulnfix-classification/resolve/main/eval_results.json
- Command line
-
hf download hf://ecwk/starencoder-vulnfix-classification/eval_results.json
-
curl -L -o eval_results.json https://huggingface.co/ecwk/starencoder-vulnfix-classification/resolve/main/eval_results.json
383 Bytes
| { | |
| "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 | |
| } |