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vulnerability-severity-classification-chinese-macbert-base

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Computer Incident Response Center Luxembourg 24

This PR significantly enhances the model card for vulnerability-severity-classification-chinese-macbert-base by:

• Adding pipeline_tag: text-classification and language: zh to the metadata for improved discoverability and accurate filtering on the Hugging Face Hub.
• Including more descriptive tags such as text-classification, classification, nlp, chinese, and vulnerability.
• Updating the main title to VLAI: A RoBERTa-Based Model for Automated Vulnerability Severity Classification to align with the associated research paper.
• Adding a clear description of the model based on the paper's abstract.
• Providing direct links to the paper (VLAI: A RoBERTa-Based Model for Automated Vulnerability Severity Classification), the project page (https://vulnerability.circl.lu), and the associated GitHub repository (https://github.com/vulnerability-lookup/ML-Gateway).
• Adding a practical Python sample usage snippet using the transformers library, including an example with Chinese text.
• Removing the auto-generated comment as the model card has now been manually improved.

These additions provide users with richer context and make the model more accessible and understandable.