Update app.py

app.py

@@ -55,12 +55,6 @@ def broad_scope_class_predictor(class_embeddings, abstract_embedding, N=5, Sensi
     HighestSimilarity = predictions.nlargest(N, ['Score'])
 
 def sentence_embedder(sentences, model_path):
-  """
-  Calling the sentence similarity model to generate embeddings on input text.
-  :param sentences: takes input text in the form of a string
-  :param model_path: path to the text similarity model
-  :return returns a (1, 384) embedding of the input text
-  """
   tokenizer = AutoTokenizer.from_pretrained(model_path) #instantiating the sentence embedder using HuggingFace library
   model = AutoModel.from_pretrained(model_path, from_tf=True) #making a model instance
   encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')