Update with notebook

src/app.py

@@ -335,14 +335,33 @@ def create_demo_interface():
                         show_label=False,
                     )
 
-                gr.Markdown(
-                    """
-                    **Key Findings:**
-                    - Qwen2.5-VL-72B-SFT achieves >95% accuracy on masterCategory
-                    - Fine-tuned model shows 18% improvement on subCategory vs base model
-                    - All models maintain >90% precision and recall on gender classification
-                    """
-                )
+            with gr.Row():
+                with gr.Column():
+                    gr.Markdown(
+                        """
+                        **Key Findings:**
+                        - Qwen2.5-VL-72B-SFT achieves >95% accuracy on masterCategory
+                        - Fine-tuned model shows 18% improvement on subCategory vs base model
+                        - All models maintain >90% precision and recall on gender classification
+                        """
+                    )
+                with gr.Column():
+                    gr.Markdown(
+                        """
+                        ### 🚀 Want to Fine-Tune Your Own Model? 🚀
+
+                        Check out our comprehensive fine-tuning cookbook to learn how we built this model!
+                        The notebook covers:
+                        - Dataset preparation and exploration
+                        - Data preprocessing for VLM fine-tuning
+                        - Fine-tuning with Fireworks AI
+                        - Model evaluation and deployment
+
+                        **[📓 Open Fine-Tuning Notebook](../notebooks/01-eda-and-fine-tuning.ipynb)**
+
+                        Perfect for adapting this approach to your own product catalog or domain-specific use case.
+                        """
+                    )
 
     return demo