This RoBERTa model is trained on Devign for code vulnerability detection. It is a binary classification model.

Code example:

from transformers import AutoTokenizer, AutoModelForSequenceClassification

from transformers import pipeline

tokenizer = AutoTokenizer.from_pretrained("Rojic/VulRoBERTa",trust_remote_code=True)

model = AutoModelForSequenceClassification.from_pretrained("Rojic/VulRoBERTa")

pipe = pipeline("text-classification", tokenizer=tokenizer,model=model, trust_remote_code=True, return_all_scores=True)

#pipe(code)

pipe("static void filter_mirror_setup(NetFilterState *nf, Error **errp)\n{\n MirrorState *s = FILTER_MIRROR(nf);\n Chardev *chr;\n chr = qemu_chr_find(s->outdev);\n if (chr == NULL) {\n error_set(errp, ERROR_CLASS_DEVICE_NOT_FOUND,\n "Device '%s' not found", s->outdev);\n qemu_chr_fe_init(&s->chr_out, chr, errp);")

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