Update app.py

app.py

@@ -68,6 +68,11 @@ from datasets import load_dataset
 from huggingface_hub import HfApi, list_models
 import os
 from huggingface_hub import HfFileSystem
+from tensorflow.keras.models import Sequential, model_from_json
+import tensorflow_datasets as tfds
+import tensorflow as tf
+
+tfds.disable_progress_bar()
 
 # dataset = load_dataset('Seetha/Visualization', streaming=True)
 # df = pd.DataFrame.from_dict(dataset['train'])
@@ -153,12 +158,19 @@ def main():
       class_list.append(i['word'])
       entity_list.append(i['entity_group'])
   
-  filename = 'Checkpoint-classification.sav'
-  loaded_model = pickle.load(open(filename, 'rb'))
-  loaded_vectorizer = pickle.load(open('vectorizefile_classification.pickle', 'rb'))
-
-  pipeline_test_output = loaded_vectorizer.transform(class_list)
-  predicted = loaded_model.predict(pipeline_test_output)
+  # filename = 'Checkpoint-classification.sav'
+  # loaded_model = pickle.load(open(filename, 'rb'))
+  # loaded_vectorizer = pickle.load(open('vectorizefile_classification.pickle', 'rb'))
+
+  # pipeline_test_output = loaded_vectorizer.transform(class_list)
+  # predicted = loaded_model.predict(pipeline_test_output)
+  json_file = open('model.json', 'r')
+  loaded_model_json = json_file.read()
+  json_file.close()
+  loaded_model = model_from_json(loaded_model_json)
+  # load weights into new model
+  loaded_model.load_weights("model.h5")
+    
   pred1 = predicted
   level0 = []
   count =0