Text Classification
Transformers
Safetensors
code
roberta
codebert
vulnerability-detection
cybersecurity
software-security
static-analysis
text-embeddings-inference
Instructions to use Khansa-saAI-29/final-codebert-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Khansa-saAI-29/final-codebert-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Khansa-saAI-29/final-codebert-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Khansa-saAI-29/final-codebert-model") model = AutoModelForSequenceClassification.from_pretrained("Khansa-saAI-29/final-codebert-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| language: | |
| - code | |
| library_name: transformers | |
| pipeline_tag: text-classification | |
| base_model: microsoft/codebert-base | |
| datasets: | |
| - DiverseVul | |
| tags: | |
| - codebert | |
| - vulnerability-detection | |
| - cybersecurity | |
| - software-security | |
| - static-analysis | |
| - transformers | |
| metrics: | |
| - accuracy | |
| - precision | |
| - recall | |
| - f1 | |
| # Fine-tuned CodeBERT for Vulnerability Detection--- | |
| license: apache-2.0 | |
| base_model: | |
| - microsoft/codebert-base | |
| library_name: transformers | |
| --- | |
| # Fine-tuned CodeBERT for Vulnerability Detection | |
| ## Description | |
| This model is fine-tuned on the Big-Vul dataset for binary vulnerability classification. | |
| Labels: | |
| - 0 = Non-Vulnerable | |
| - 1 = Vulnerable | |
| Base model: | |
| microsoft/codebert-base | |
| Framework: | |
| Transformers + PyTorch |