Update app.py

app.py

@@ -1,13 +1,25 @@
 import streamlit as st
+import transformers
 from transformers import pipeline
+from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
 
-pipe = pipeline('sentiment-analysis')
-text = st.text_area('enter some text!')
+model_name = 'deepset/xlm-roberta-large-squad2'
+
+model = AutoModelForQuestionAnswering.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+# a) Get predictions
+ctx  = st.text_area('Gib context')
+q = st.text_area('Gib question')
+
+nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
+#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(context=ctx, question=q)
+st.json(res["answer"])
 
-if text: 
- out = pipe(text)
- st.json(out)
-  
 #from transformers import pipeline
 
 #model_name = "deepset/xlm-roberta-large-squad2"