Update pipeline.py

pipeline.py

@@ -14,15 +14,6 @@ class PreTrainedPipeline():
         self.model = joblib.load((os.path.join(path, "pipeline.pkl"))
 
     def __call__(self, inputs: str) -> List[Dict[str, float]]:
-        """
-        Args:
-            inputs (:obj:`str`):
-                a string containing some text
-        Return:
-            A :obj:`list`:. The object returned should be a list of one list like [[{"label": 0.9939950108528137}]] containing:
-                - "label": A string representing what the label/class is. There can be multiple labels.
-                - "score": A score between 0 and 1 describing how confident the model is for this label/class.
-        """
         predictions = self.model.predict_proba([inputs])
         labels = []
         for cls in predictions[0]: