Instructions to use alfonsusrr/BugBERTa-C with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alfonsusrr/BugBERTa-C with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alfonsusrr/BugBERTa-C")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alfonsusrr/BugBERTa-C") model = AutoModelForSequenceClassification.from_pretrained("alfonsusrr/BugBERTa-C", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| language: | |
| - en | |
| datasets: | |
| - Rtian/DebugBench | |
| metrics: | |
| - roc_auc | |
| - accuracy | |
| pipeline_tag: text-classification | |
| This model is trained on base model `microsoft/codebert-base` added with classification head and trained with `DebugBench` dataset for bug classification purpose. |