update handler

handler.py

@@ -8,7 +8,7 @@ class EndpointHandler():
         # Preload all the elements you are going to need at inference.
         # pseudo:
         # self.model= load_model(path)
-        self.md_model = AltCLIPModel.from_pretrained(path)
+        self.md_model = AltCLIPModel.from_pretrained(path).to(device)
         self.md_processor = AltCLIPProcessor.from_pretrained(path)
 
 
@@ -25,6 +25,6 @@ class EndpointHandler():
         # self.model(input)
         with torch.inference_mode():
             texts = data.pop("inputs",data)
-            inputs = self.md_processor(text = texts, padding=True, return_tensors="pt")
+            inputs = self.md_processor(text = texts, padding=True, return_tensors="pt").to(device)
             text_feature = self.md_model.get_text_features(**inputs)
         return {"feature":text_feature}