test

app.py

@@ -357,7 +357,7 @@ class CVEDashboard:
 
 def generate_tailored_summary(cve_description: str, audience: str, hf_token: Optional[str] = None, max_retries: int = 2) -> str:
     """
-    Generates a tailored CVE summary using google/gemma-2-9b-it via HuggingFace Inference API.
+    Generates a tailored CVE summary using google/gemma-2-2b-it via HuggingFace Inference API.
     
     Args:
         cve_description: The original CVE description
@@ -382,7 +382,7 @@ def generate_tailored_summary(cve_description: str, audience: str, hf_token: Opt
     
     # Define the model(s) to use
     models = [
-        "google/gemma-2-9b-it",
+        "google/gemma-2-2b-it",
     ]
     
     headers = {"Authorization": f"Bearer {token}"}
@@ -594,7 +594,7 @@ def create_interface():
                             - Search CVEs by date range and keywords
                             - Filter by severity levels
                             - Visualize CVE distributions and trends
-                            - AI-powered audience-specific summaries using the google/gemma-2-9b-it model.
+                            - AI-powered audience-specific summaries using the google/gemma-2-2b-it model.
                             
                             **Supported Audiences:**
                             - **Cybersecurity Professional:** Focus on threats, attack vectors, and mitigation
@@ -606,7 +606,7 @@ def create_interface():
                             
                             **Data Source:** [NIST NVD API](https://nvd.nist.gov/developers/vulnerabilities)
                             
-                            **AI Model:** [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it)
+                            **AI Model:** [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it)
 
                             **Disclaimer:** Generated content may be inaccurate or false.