translation with pretrained model

app.py

@@ -1,20 +1,14 @@
 import streamlit as st
 from transformers import pipeline
-from PIL import Image
 
-pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
+translator = pipeline("translation_vi_to_en", model="Helsinki-NLP/opus-mt-vi-en")
 
-st.title("Hot Dog? Or Not?")
+st.title("Demo translation with pretrained model")
 
-file_name = st.file_uploader("Upload a hot dog candidate image")
+input_text = st.text_area("Nhập văn bản tiếng Việt:", "")
 
-if file_name is not None:
-    col1, col2 = st.columns(2)
+if input_text:
+    translated_text = translator(input_text)
 
-    image = Image.open(file_name)
-    col1.image(image, use_column_width=True)
-    predictions = pipeline(image)
-
-    col2.header("Probabilities")
-    for p in predictions:
-        col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%")
+    st.write("Translation Vietnamese to English:")
+    st.write(translated_text[0]["translation_text"])