Update app.py

app.py

@@ -1,17 +1,19 @@
-import streamlit as st
-from transformers import pipeline
+from transformers import AutoModelWithLMHead, AutoTokenizer
 
-classifier = pipeline("text2text-generation", model="mrm8488/t5-base-finetuned-question-generation-ap")
-def main():
-    st.title("English to German")
+tokenizer = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-question-generation-ap")
+model = AutoModelWithLMHead.from_pretrained("mrm8488/t5-base-finetuned-question-generation-ap")
 
-    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)
+def get_question(answer, context, max_length=64):
+  input_text = "answer: %s  context: %s </s>" % (answer, context)
+  features = tokenizer([input_text], return_tensors='pt')
 
-if __name__ == "__main__":
-    main()
+  output = model.generate(input_ids=features['input_ids'], 
+               attention_mask=features['attention_mask'],
+               max_length=max_length)
+
+  return tokenizer.decode(output[0])
+
+context = "Manuel has created RuPERTa-base with the support of HF-Transformers and Google"
+answer = "Manuel"
+
+get_question(answer, context)