dbristol/aisec_model_v1
dbristol/aisec_model_v1 is a 7 billion parameter Mistral-7B-Instruct-v0.3 model fine-tuned by dbristol using LoRA. This specialized model excels at cross-framework AI security and risk management analysis, integrating NIST AI RMF 1.0, MITRE ATLAS, OWASP AI Exchange, and Google SAIF. It is optimized for generating structured analysis and documentation for AI governance and security practitioners.
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AI Security Framework Expert (aisec_model_v1)
dbristol/aisec_model_v1 is a specialized 7 billion parameter language model, fine-tuned from mistralai/Mistral-7B-Instruct-v0.3 using Low-Rank Adaptation (LoRA) on Apple Silicon. Only 0.145% of the base model's parameters were updated, focusing its expertise on AI security and risk management across key industry frameworks.
Key Capabilities
- Cross-Framework Analysis: Provides integrated analysis across NIST AI RMF 1.0, MITRE ATLAS, OWASP AI Exchange, and Google SAIF.
- Structured Output: Designed to generate structured insights for AI governance, risk, and compliance.
- Domain-Specific Knowledge: Optimized for tasks like mapping AI system risks, identifying MITRE ATLAS TTPs, drafting OWASP AI Exchange controls, and cross-referencing Google SAIF responsibilities.
- Performance: Achieved a validation loss of 0.216 during LoRA fine-tuning, indicating strong specialization in its target domain.
Good For
- Security practitioners and researchers needing to analyze AI system risks.
- AI governance professionals requiring structured documentation and framework mapping.
- Generating insights for specific AI security frameworks simultaneously.
This model is intended to augment human expertise, not replace it, and responses should always be verified against official documentation.