Update app.py

app.py

@@ -1,10 +1,7 @@
-from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
 import streamlit as st
+from transformers import pipeline
 
-model_name = "deepset/roberta-base-squad2"
-
-# a) Get predictions
-nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
+classifier = pipeline("translation", model="t5-small")
 def main():
     st.title("English to German")
 
@@ -17,14 +14,4 @@ def main():
           st.json(results)
 
 if __name__ == "__main__":
-    main()
-
-QA_input = {
-    'question': 'Why is model conversion important?',
-    'context': 'The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks.'
-}
-res = nlp(QA_input)
-
-# b) Load model & tokenizer
-model = AutoModelForQuestionAnswering.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
+    main()