Update README.md

README.md

@@ -98,6 +98,42 @@ While AIRealNet performs exceptionally well on typical AI-generated images, user
 
 ---
 
+## Demo and Usage
+
+1. **Installing dependecies**
+
+```python
+pip install -U transformers
+```
+2. **Loading and running a demo**
+
+```python
+from transformers import pipeline
+
+pipe = pipeline("image-classification", model="XenArcAI/AIRealNet")
+pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# example image
+```
+# Demo
+
+* **Given Image**(Checkout Maths best filtered dataset focused on reasoning on XenArcAI)
+
+<p align="center">
+  <img 
+    src="https://cdn-uploads.huggingface.co/production/uploads/677fcdf29b9a9863eba3f29f/eVkKUTdiInUl6pbIUghQC.png" 
+    alt="AIRealNet Banner" 
+    width="90%" 
+    style="border-radius:15px;"
+  />
+</p>
+
+* **Model Output**
+
+```bash
+[{'label': 'artificial', 'score': 0.9865425825119019},
+ {'label': 'real', 'score': 0.013457471504807472}]
+```
+**Note** its correct as the image was generated by a diffusion model
+
 ## Intended Use
 
 * Detect AI-generated imagery on social media, research publications, and digital media platforms.