Update app.py

app.py

@@ -36,8 +36,8 @@ print ("before main")
 st.title("Transformers Interpet Demo App")
 print ("before main")
 
-image = Image.open("./images/tight@1920x_transparent.png")
-st.sidebar.image(image, use_column_width=True)
+#image = Image.open("./images/tight@1920x_transparent.png")
+#st.sidebar.image(image, use_column_width=True)
 st.sidebar.markdown(
  "Check out the package on [Github](https://github.com/cdpierse/transformers-interpret)"
 )
@@ -63,23 +63,7 @@ model_name = st.sidebar.selectbox(
  "Choose a classification model", list(models.keys())
 )
 model, tokenizer = load_model(model_name)
-print ("Model loaded")
-if model_name.startswith("textattack/"):
- model.config.id2label = {0: "NEGATIVE (0) ", 1: "POSITIVE (1)"}
-model.eval()
-print ("Model Evaluated")
-cls_explainer = SequenceClassificationExplainer(model=model, tokenizer=tokenizer)
-print ("Model Explained")
-if cls_explainer.accepts_position_ids:
- emb_type_name = st.sidebar.selectbox(
- "Choose embedding type for attribution.", ["word", "position"]
- )
- if emb_type_name == "word":
- emb_type_num = 0
- if emb_type_name == "position":
- emb_type_num = 1
-else:
- emb_type_num = 0
+