add test handler

handler.py

@@ -0,0 +1,22 @@
+from typing import Dict, List, Any
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+class EndpointHandler():
+    def __init__(self, path=""):
+        # Preload all the elements you are going to need at inference.
+        # pseudo:
+        self.tokenizer= AutoTokenizer.from_pretrained(path)
+        self.model= AutoModelForCausalLM.from_pretrained(path)
+
+    def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
+        """
+       data args:
+            inputs (:obj: `str` | `PIL.Image` | `np.array`)
+            kwargs
+      Return:
+            A :obj:`list` | `dict`: will be serialized and returned
+        """
+        text = data.pop("text")
+        inputs = self.tokenizer(text, return_tensors="pt")
+        logits = self.model(inputs).logits
+        return [{"predictions":logits.argmax(dim=-1)}]