Update app.py

app.py

@@ -81,57 +81,6 @@ if cls_explainer.accepts_position_ids:
 else:
  emb_type_num = 0
 
-explanation_classes = ["predicted"] + list(model.config.label2id.keys())
-explanation_class_choice = st.sidebar.selectbox(
- "Explanation class: The class you would like to explain output with respect to.",
- explanation_classes,
-)
-my_expander = st.beta_expander(
- "Click here for a description of models and their tasks"
-)
-with my_expander:
- st.json(models)
-
-# st.info("Max char limit of 350 (memory management)")
-text = st.text_area(
- "Enter text to be interpreted",
- "I like you, I love you",
- height=400,
- max_chars=850,
-)
-print ("Before button")
-if st.button('Say hello'):
- st.write('Why hello there')
-else:
- st.write('Goodbye')
-print ("After test button")
 
-if st.button("Interpret Text"):
- #print_memory_usage()
- st.text("Output")
- with st.spinner("Interpreting your text (This may take some time)"):
- print ("Interpreting text")
- if explanation_class_choice != "predicted":
- word_attributions = cls_explainer(
- text,
- class_name=explanation_class_choice,
- embedding_type=emb_type_num,
- internal_batch_size=2,
- )
- else:
- word_attributions = cls_explainer(
- text, embedding_type=emb_type_num, internal_batch_size=2
- )
 
- if word_attributions:
- print ("Word Attributions")
- word_attributions_expander = st.beta_expander(
- "Click here for raw word attributions"
- )
- with word_attributions_expander:
- st.json(word_attributions)
- components.v1.html(
- cls_explainer.visualize()._repr_html_(), scrolling=True, height=350
- )
- print ("end of stuff")
 print ("end of total file")