Text Classification
Transformers
Safetensors
code
roberta
codebert
vulnerability-detection
cybersecurity
software-security
static-analysis
text-embeddings-inference
# 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")Quick Links
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
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Model tree for Khansa-saAI-29/final-codebert-model
Base model
microsoft/codebert-base
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Khansa-saAI-29/final-codebert-model")