Update app.py

app.py

@@ -35,21 +35,21 @@ max_words = 2000
 max_len = 111
 
 # load the model from disk
-filename = 'resil_lstm_model.sav'
-lmodel = pickle.load(open(filename, 'rb'))
+#filename = 'resil_lstm_model.sav'
+#lmodel = pickle.load(open(filename, 'rb'))
 
 # load the model from disk
-filename = 'tokenizer.pickle'
-tok = pickle.load(open(filename, 'rb'))
+#filename = 'tokenizer.pickle'
+#tok = pickle.load(open(filename, 'rb'))
 
 def process_final_text(text):
     X_test = str(text).lower()
-    l = []
-    l.append(X_test)
-    test_sequences = tok.texts_to_sequences(l)
-    test_sequences_matrix = sequence.pad_sequences(test_sequences,maxlen=max_len)
-    lstm_prob = lmodel.predict(test_sequences_matrix.tolist()).flatten()
-    lstm_pred = np.where(lstm_prob>=0.5,1,0)
+    #l = []
+    #l.append(X_test)
+    #test_sequences = tok.texts_to_sequences(l)
+    #test_sequences_matrix = sequence.pad_sequences(test_sequences,maxlen=max_len)
+    #lstm_prob = lmodel.predict(test_sequences_matrix.tolist()).flatten()
+    #lstm_pred = np.where(lstm_prob>=0.5,1,0)
     
     encoded_input = tokenizer(X_test, return_tensors='pt')
     output = model(**encoded_input)
@@ -101,7 +101,7 @@ with gr.Blocks(title=title) as demo:
     gr.Markdown(description1)
     gr.Markdown("""---""")
     prob1 = gr.Textbox(label="Enter Your Text Here:",lines=2, placeholder="Type it here ...")
-    submit_btn = gr.Button("Create & Analyze")
+    submit_btn = gr.Button("Analyze")
     #text = gr.Textbox(label="Text:",lines=2, placeholder="Please enter text here ...")
     #submit_btn2 = gr.Button("Analyze")