Text Classification
Transformers
PyTorch
JAX
Safetensors
roberta
Text Classification
Transformers
PyTorch
JAX
MSR
English
Inference Endpoints
text-embeddings-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("starmage520/Coderbert_finetuned_detect_vulnerability_on_MSR")
model = AutoModelForSequenceClassification.from_pretrained("starmage520/Coderbert_finetuned_detect_vulnerability_on_MSR")Quick Links
I finetuned a RobertaForSequenceClassification model which is initialized from CodeBert [https://huggingface.co/microsoft/codebert-base] to judge whether a code is vulnerable or not. I selected balanced samples from MSR dataset [https://github.com/ZeoVan/MSR_20_Code_vulnerability_CSV_Dataset] for training, validation, and testing. The "func_before" is used for code classification. All the data is in the file "msr.csv".
Test Reulsts: acc 0.7022935779816514, f1 0.6482384823848238, precision 0.7920529801324503, recall 0.5486238532110091
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="starmage520/Coderbert_finetuned_detect_vulnerability_on_MSR")