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handler.py

@@ -28,7 +28,9 @@ class EndpointHandler():
 
         # Get embeddings
         with torch.no_grad():
-            image_features = self.model.get_image_features(**inputs)
+            outputs = self.model(**inputs)
+            # Get global image embedding by averaging the last hidden states
+            image_features = outputs.last_hidden_state.mean(dim=1)
 
         # Calculate similarity if 2 images provided
         if len(images) == 2: