Text Classification
Transformers
Safetensors
English
roberta
cybersecurity
vulnerability
cwe
cve
nvd
Eval Results (legacy)
text-embeddings-inference
Instructions to use xamxte/cwe-classifier-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xamxte/cwe-classifier-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xamxte/cwe-classifier-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xamxte/cwe-classifier-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("xamxte/cwe-classifier-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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@@ -181,12 +181,18 @@ This model predicts **specific (child) CWE categories** where possible. For exam
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- **Description-based**: Uses only the text description, not CVSS scores, CPE, or other metadata.
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- **Single-label**: Predicts one CWE per CVE, though some vulnerabilities may involve multiple weakness types.
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## Citation
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```bibtex
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@
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title={
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url={https://huggingface.co/xamxte/cwe-classifier-roberta-base}
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}
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```
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- **Description-based**: Uses only the text description, not CVSS scores, CPE, or other metadata.
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- **Single-label**: Predicts one CWE per CVE, though some vulnerabilities may involve multiple weakness types.
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## Paper
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📄 **[Fine-tuning RoBERTa for CVE-to-CWE Classification: A 125M Parameter Model Competitive with LLMs](https://arxiv.org/abs/2603.14911)**
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## Citation
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```bibtex
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@article{mosievskiy2026cwe,
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title={Fine-tuning RoBERTa for CVE-to-CWE Classification: A 125M Parameter Model Competitive with LLMs},
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author={Mosievskiy, Nikita},
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journal={arXiv preprint arXiv:2603.14911},
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year={2026}
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url={https://huggingface.co/xamxte/cwe-classifier-roberta-base}
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}
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```
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