Update app.py

app.py

@@ -107,26 +107,26 @@ def tokenize(text):
 model = model_()
 model.load_weights("cutto_tf2.h5")
 st.title("Cutto Thai word seggmentation.")
-multi = '''# Score
+text = st.text_area("Enter original text!")
+if st.button("cut it!!"):
+    if text:
+        words = tokenize(text)
+        st.subheader("seggemt:")
+        st.write('|'.join(words))
+    else:
+        st.warning("Please enter some text to seggmentation")
+
+multi = '''### Score
 Evaluate the model performance using the test dataset divided from BEST CORPUS 2009, which comprises 10 percent, with the following scores:
 - F1-Score: 98.37		
 - Precision: 98.02
 - Recall: 98.67
 
-# Resource Funding
+### Resource Funding
 NSTDA Supercomputer center (ThaiSC) and the National e-Science Infrastructure Consortium for their support of computer facilities.
 
-# Citation
+### Citation
 If you use cutto in your project or publication, please cite the model as follows:
 ปรีชานนท์ ชาติไทย และ สัจจวัจน์ ส่งเสริม. (2567), การสรุปข้อความข่าวภาษาไทยด้วยโครงข่ายประสาทเทียม (Thai News Text Summarization Using Neural Network), วิทยาศาสตรบัณฑิต (วทบ.):ขอนแก่น, มหาวิทยาลัยขอนแก่น
 '''
-st.markdown(multi)
-text = st.text_area("Enter original text!")
-if st.button("cut it!!"):
-    if text:
-        words = tokenize(text)
-        st.subheader("seggemt:")
-        st.write('|'.join(words))
-    else:
-        st.warning("Please enter some text to seggmentation")
-        
+st.markdown(multi)