update app

app.py

@@ -6,6 +6,14 @@ import streamlit as st
 from transformers import AutoModelForSequenceClassification,AutoTokenizer,pipeline
 from transformers_interpret import SequenceClassificationExplainer
 
+@st.cache
+def visualize(text):
+
+     cls_explainer = SequenceClassificationExplainer(model,tokenizer)
+     word_attributions = cls_explainer(masked_text)
+     cls_explainer.visualize('visualize.html')
+
+
 @st.cache
 def load_model(text):
     
@@ -20,7 +28,7 @@ def load_model(text):
   
     results = nlp(text)
     
-    return results,model,tokenizer
+    return results
     #MASK_TOKEN = tokenizer.mask_token
     #masked_text = masked_text.replace("<mask>", MASK_TOKEN)
     #result_sentence = nlp(masked_text)
@@ -58,10 +66,9 @@ def app():
 
             if st.button('Visualize attributions'):
                 with st.spinner("Visualizing .....") :
+                    visualize(masked_text)
 
-                    cls_explainer = SequenceClassificationExplainer(model,tokenizer)
-                    word_attributions = cls_explainer(masked_text)
-                    st.write(cls_explainer.visualize())
+                   
 
 if __name__ == "__main__":
     app()