added custom handler

handler.py

@@ -0,0 +1,16 @@
+from typing import Dict, List, Any
+from transformers import AutoModel, pipeline
+
+class EndpointHandler:
+    def __init__(self, path=""):
+        # load the model
+        model = AutoModel.from_pretrained(path, low_cpu_mem_usage=True)
+        # create inference pipeline
+        # Do I have to check device?
+        self.pipeline = pipeline("text-generation", model=model)
+
+    # (Might have to adjust typing)
+    def __call__(self, data: Any) -> List[List[Dict[str, float]]]:
+        inputs = data.pop("inputs", data)  # Should I get and pass parameters?
+        prediction = self.pipeline(inputs)
+        return prediction

requirements.txt

@@ -0,0 +1 @@
+transformers

test.py

@@ -0,0 +1,13 @@
+from handler import EndpointHandler
+
+# init handler
+my_handler = EndpointHandler(path=".")
+
+# prepare sample payload
+payload = {"inputs": "I am Bob and I want to "}
+
+# test the handler
+pred=my_handler(payload)
+
+# show results
+print("pred", pred)