Update app.py

app.py

@@ -4,7 +4,12 @@ import tensorflow as tf
 def split_char(text):
   return " ".join(list(text))
   
-!unzip Universal_sentence_encoder_Tribrid_embedding_model-20220920T213455Z-001.zip
+# Unzipping model 
+import zipfile
+zip_ref = zipfile.ZipFile(Universal_sentence_encoder_Tribrid_embedding_model-20220920T213455Z-001.zip, "r")
+  zip_ref.extractall()
+  zip_ref.close()
+
 
 from spacy.lang.en import English
 
@@ -51,7 +56,6 @@ def make_predictions(Input):
   
   # Loading in model and getting a summary of loaded model
   #skimlit_universal_sentence_encoder_model=tf.keras.models.load_model("/content/drive/MyDrive/skimlit_models/Universal_sentence_encoder_Tribrid_embedding_model")
-  skimlit_universal_sentence_encoder_model=Universal_sentence_encoder_Tribrid_embedding_model-20220920T213455Z-001
 
   # Making prediction with loaded model on sample abstract
   abstract_pred_probs=skimlit_universal_sentence_encoder_model.predict(x=(abstract_line_number_one_hot,