Text Classification
Transformers
Safetensors
roberta
code-defect-detection
c
text-embeddings-inference
Instructions to use lafarizo/code_defect_detection_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lafarizo/code_defect_detection_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lafarizo/code_defect_detection_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lafarizo/code_defect_detection_v1") model = AutoModelForSequenceClassification.from_pretrained("lafarizo/code_defect_detection_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
title: Code Defect Detection v1
tags:
- code-defect-detection
- c
library_name: transformers
datasets:
- semeru/code-code-DefectDetection
Code Defect Detection v1
Code Defect Detection for C language
Model Sources
Dataset
- Repository: semeru/code-code-DefectDetection
| Results | Value |
|---|---|
| Evaluation Loss | 0.7605 |
| Accuracy | 66.76% |
| Precision | 65.64% |
| Recall | 58.01% |
| F1 Score | 61.59% |
| AUC | 73.52% |