Upload pipeline.py

pipeline.py

@@ -12,8 +12,8 @@ class PreTrainedPipeline():
         """
         self.bert_tokenizer = BertTokenizer.from_pretrained("bert-base-uncased")
         self.model = FoodyBertForSequenceClassification.from_pretrained("rttl-ai/foody-bert")
-    def __call__(self, inputs: str) -> List[float]:
-
+    #def __call__(self, inputs: str) -> List[float]:
+    def __call__(self, inputs: str) -> str:
         """
         Args:
             inputs (:obj:`str`):
@@ -27,4 +27,4 @@ class PreTrainedPipeline():
             predicted_class_id = self.model(X).logits.argmax().item()
             labels = ['positive','neutral','negative']
             reps   = labels[predicted_class_id]
-        return predicted_class_id
+        return reps