Update app.py

app.py

@@ -1,17 +1,5 @@
-import streamlit as st
-from transformers import pipeline
+from transformers import AutoTokenizer, T5ForConditionalGeneration
 
-classifier = pipeline("table-question-answering", model="google/tapas-base-finetuned-wtq")
-def main():
-    st.title("English to German")
-
-    with st.form("text_field"):
-        text = st.text_area('enter some english word:')
-        # clicked==True only when the button is clicked
-        clicked = st.form_submit_button("Submit")
-        if clicked:
-          results = classifier([text])
-          st.json(results)
-
-if __name__ == "__main__":
-    main()
+model_name = "google/tapas-base-finetuned-wtq" # you can specify the model size here
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = T5ForConditionalGeneration.from_pretrained(model_name)