Update app.py

app.py

@@ -1,33 +1,33 @@
 import streamlit as st
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
-# Ensure the model and tokenizer are available
-tokenizer = AutoTokenizer.from_pretrained("facebook/mbart-large-50", use_fast=True)
+# Load model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("facebook/mbart-large-50")
 model = AutoModelForSeq2SeqLM.from_pretrained("facebook/mbart-large-50")
 
 def translate_to_japanese(english_text):
-    # Translation prompt
-    input_text = f"translate English to Japanese: {english_text}"
+    # Add language tokens for translation (from English > to Japanese)
+    input_text = f">en< {english_text} </s>"
 
     # Tokenize input text
     inputs = tokenizer(input_text, return_tensors="pt", padding=True, truncation=True)
 
-    # Generate translation
+    # Generate translation (the model's output should be a token sequence for the translation)
     outputs = model.generate(inputs['input_ids'], max_length=128, num_beams=4, early_stopping=True)
 
     # Decode the generated token IDs into a string
     translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    
+
     return translated_text
 
 # Streamlit UI
 st.title("English to Japanese Translator")
 st.write("This app translates English sentences to Japanese using the mBART model.")
 
-# User input
+# Create an input box for the user to enter an English sentence
 english_sentence = st.text_area("Enter English sentence:", "")
 
-# Translate and display result
+# Translate and display the result
 if english_sentence:
     with st.spinner("Translating..."):
         translation = translate_to_japanese(english_sentence)