Create handler.py

handler.py

@@ -0,0 +1,26 @@
+from typing import Dict, List, Any
+from setfit import SetFitModel
+
+class EndpointHandler:
+    def __init__(self, path=""):
+        # load model
+        self.model = SetFitModel.from_pretrained(path)
+
+        self.id2label = {{0: 'Art', 1: 'Dedicated', 2: 'Domains', 3: 'Gaming', 4: 'General', 5: 'Music', 6: 'Other'}}
+
+    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
+        """
+        # get inputs
+        inputs = data.pop("inputs", data)
+        if isinstance(inputs, str):
+            inputs = [inputs]
+
+        # run normal prediction
+        scores = self.model.predict_proba(inputs)[0]
+
+        return [{"label": self.id2label[i], "score": score.item()} for i, score in enumerate(scores)]