| Model Type |  | 
| Use Cases | 
| Areas: | | Source code vulnerability detection, Security research | 
 |  | Applications: | | Developer workflows, Code review processes, Standalone security tool | 
 |  | Primary Use Cases: | | Identifying security vulnerabilities in source code | 
 |  | Limitations: | | May not identify all vulnerabilities if multiple are present, Prone to false positives, Results should be verified by human experts, Affected by code complexity and context | 
 |  | Considerations: | | Should be integrated within a broader security review process. | 
 |  | 
| Supported Languages | | Go (High), Python (High), C (High), C++ (High), Fortran (High), Ruby (High), Java (High), Kotlin (High), C# (High), PHP (High), Swift (High), JavaScript (High), TypeScript (High) | 
 | 
| Training Details | 
| Data Sources: | | Proprietary dataset for vulnerability detection | 
 |  | Methodology: | | Fine-tuned for vulnerability detection; trained using Parameter-Efficient Fine-Tuning (PEFT). | 
 |  | Hardware Used: |  |  | 
| Input Output | 
| Input Format: | | Programming code snippets | 
 |  | Accepted Modalities: |  |  | Output Format: | | Textual analysis of vulnerabilities and quality issues | 
 |  | Performance Tips: | | Best performance with appropriate input code snippet length. | 
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