"Update model card with complete documentation"

README.md

@@ -1,16 +1,42 @@
 ---
+language: en
 tags:
-  - image-classification
-  - computer-vision
-  - ai-detection
-  - transformers
-library_name: transformers
-model_type: vit
-license: apache-2.0
-datasets:
-  - custom-dataset
-metrics:
-  - accuracy
-  - precision
-  - recall
+- image-classification
+- ai-detection
+- vit
+license: mit
 ---
+
+# AI Image Detector
+
+## Model Description
+This model is designed to detect whether an image is real or AI-generated. It uses Vision Transformer (VIT) architecture to provide accurate classification.
+
+## Model Usage
+```python
+from transformers import ViTImageProcessor, ViTForImageClassification
+from PIL import Image
+import torch
+
+# Load model and processor
+processor = ViTImageProcessor.from_pretrained("yaya36095/ai-image-detector")
+model = ViTForImageClassification.from_pretrained("yaya36095/ai-image-detector")
+
+def detect_image(image_path):
+    # Open image
+    image = Image.open(image_path)
+    
+    # Process image
+    inputs = processor(images=image, return_tensors="pt")
+    
+    # Get predictions
+    with torch.no_grad():
+        outputs = model(**inputs)
+        predictions = outputs.logits.softmax(dim=-1)
+    
+    # Get result
+    prediction_id = torch.argmax(predictions).item()
+    confidence = predictions[0][prediction_id].item() * 100
+    
+    result = "AI Generated" if prediction_id == 1 else "Real Image"
+    return result, confidence