Upload pipeline.py

pipeline.py

@@ -11,7 +11,7 @@ class PreTrainedPipeline():
         Initialize model
         """
         self.bert_tokenizer = BertTokenizer.from_pretrained("bert-base-uncased")
-        self.model = FoodyBertForSequenceClassification.from_pretrained(".")
+        self.model = FoodyBertForSequenceClassification.from_pretrained("rttl-ai/foody-bert")
     def __call__(self, inputs: str) -> List[float]:
 
         """
@@ -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 self.model.get_sentence_vector(inputs).tolist()
+        return predicted_class_id