bug_fixes

app.py

@@ -1,5 +1,6 @@
 import gradio as gr
 import tensorflow as tf
+from tensorflow.keras.models import load_model
 
 def split_char(text):
   return " ".join(list(text))
@@ -56,13 +57,13 @@ 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=tf.keras.models.load_model("Universal_sentence_encoder_Tribrid_embedding_model-20220920T213455Z-001")
+  skimlit_model=load_model("Universal_sentence_encoder_Tribrid_embedding_model")
 
   # Making prediction with loaded model on sample abstract
-  abstract_pred_probs=skimlit_universal_sentence_encoder_model.predict(x=(abstract_line_number_one_hot,
-                                                                          abstract_total_lines_one_hot,
-                                                                          tf.constant(abstract_sentences),
-                                                                          tf.constant(abstract_char)))
+  abstract_pred_probs=skimlit_model.predict(x=(abstract_line_number_one_hot,
+                                               abstract_total_lines_one_hot,
+                                               tf.constant(abstract_sentences),
+                                               tf.constant(abstract_char)))
   
   # Turning model's prediction into labels
   abstract_preds=tf.argmax(abstract_pred_probs,axis=1)