Update handler.py

handler.py

@@ -1,20 +1,26 @@
 from typing import Dict, List, Any
-from transformers import pipeline
+from setfit import SetFitModel
 
-class EndpointHandler():
+class EndpointHandler:
     def __init__(self, path=""):
-        self.pipeline = pipeline("text-classification", model=path)
+        # load model
+        self.model = SetFitModel.from_pretrained(path)
+
+        self.id2label = {{0: 'Art', 1: 'Collectibles', 2: 'Domains', 3: 'Games', 4: 'Land', 5: 'Metaverse', 6: 'Music', 7: 'Other', 8: 'PFPs', 9: 'Sports'}}
 
     def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
         """
-       data args:
-            inputs (:obj: `str`)
-
-      Return:
-            A :obj:`list` | `dict`: will be serialized and returned
+         data args:
+              inputs (:obj: `str`)
+        Return:
+              A :obj:`list` | `dict`: will be serialized and returned
         """
         # get inputs
-        inputs = data.pop("inputs",data)
+        inputs = data.pop("inputs", data)
+        if isinstance(inputs, str):
+            inputs = [inputs]
+
         # run normal prediction
-        prediction = self.pipeline(inputs)
-        return prediction
+        scores = self.model.predict_proba(inputs)[0]
+
+        return [{"label": self.id2label[i], "score": score.item()} for i, score in enumerate(scores)]