Upload handler.py

handler.py

@@ -78,17 +78,16 @@ def predict(text):
 class EndpointHandler:
     def __init__(self, path=""):
         # load model and tokenizer from path
-        tokenizer = AutoTokenizer.from_pretrained("Lin0He/text-summary-gpt2-short")
-        model = AutoModel.from_pretrained("Lin0He/text-summary-gpt2-short")
-        self.device = "cuda" if torch.cuda.is_available() else "cpu"
+        self.tokenizer = AutoTokenizer.from_pretrained("Lin0He/text-summary-gpt2-short")
+        self.model = AutoModel.from_pretrained("Lin0He/text-summary-gpt2-short")
+    
 
     def __call__(self, data: Dict[str, Any]) -> Dict[str, str]:
         # process input
         inputs = data.pop("inputs", data)
-        parameters = data.pop("parameters", None)
-
+        # process input text
         result = predict(inputs)
-        return result
+        return {"text":result}