Update app.py

app.py

@@ -12,7 +12,7 @@ import sys
 import os
 import gradio as gr
 
-model = load_model('ISCO-Coder-BERT.h5', custom_objects={'KerasLayer': hub.KerasLayer})
+model = load_model('ISCO-Coder-BERTV2.h5', custom_objects={'KerasLayer': hub.KerasLayer})
 
 bert_layer = hub.KerasLayer("https://kaggle.com/models/tensorflow/bert/TensorFlow2/en-uncased-l-12-h-768-a-12/1",trainable=True)
 
@@ -23,10 +23,12 @@ tokenizer = tokenization.FullTokenizer(vocab_file,do_lower_case)
 # Parameters
 max_seq_length = 128
 dummy_label = 100
-label_list = list(pd.read_excel('label_list.xlsx')['label_list'])
+label_list = list(pd.read_excel('label_listV2.xlsx')['label_list'])
 
 map_data = pd.read_excel("ISCO-08 EN Structure and definitions.xlsx")
 
+label_encoder = joblib.load('label_encoderV2.joblib')
+
 # Define a function to preprocess the new data
 def get_feature_new(text, max_seq_length, tokenizer, dummy_label):
     example = classifier_data_lib.InputExample(guid=None,
@@ -62,7 +64,7 @@ def preprocess_new_data(texts):
     return dataset
 def launch(text_input):
     # Load the label encoder
-    label_encoder = joblib.load('label_encoder.joblib')
+    #label_encoder = joblib.load('label_encoderV2.joblib')
 
     # Preprocess the new data
     try: