Update pipeline.py

pipeline.py

@@ -6,11 +6,8 @@ class PreTrainedPipeline():
         # Preload all the elements you are going to need at inference.
         # For instance your model, processors, tokenizer that might be needed.
         # This function is only called once, so do all the heavy processing I/O here"""
-        raise NotImplementedError(
-            "Please implement PreTrainedPipeline __init__ function"
-        )
 
-    def __call__(self, inputs: str) -> List[float]:
+    def __call__(self, inputs: str) -> str:
         """
         Args:
             inputs (:obj:`str`):
@@ -19,6 +16,4 @@ class PreTrainedPipeline():
             A :obj:`list` of floats: The features computed by the model.
         """
         # IMPLEMENT_THIS
-        raise NotImplementedError(
-            "Please implement PreTrainedPipeline __call__ function"
-        )
+        return "hello"