Updated app file

app.py

@@ -3,7 +3,7 @@ import pandas as pd
 import numpy as np
 # from scipy.special import softmax
 # import os
-from utils import run_sentiment_analysis, preprocess, integrated_gradients
+from utils import run_sentiment_analysis, preprocess
 from transformers import AutoTokenizer, AutoConfig,AutoModelForSequenceClassification
 import os
 import time
@@ -96,15 +96,9 @@ with my_expander:
             positive_score = st.metric(label='Score', value=round(results['Positive'], 4), label_visibility='collapsed')
             time.sleep(5)
             success_message.empty()
-    interpret_button = col2.button(label='Interpret',type='secondary', use_container_width=True)
-    if interpret_button:
-            ig = integrated_gradients(text, model)
-            
-            ig = ig.sum(dim=-1).squeeze().detach().numpy()[0]
-            ig = (ig - ig.min()) / (ig.max() - ig.min())
-            # Display the Integrated Gradients as a bar chart
-            st.bar_chart(ig)
+    # interpret_button = col2.button(label='Interpret',type='secondary', use_container_width=True)
 
 
 # st.help()
     # create a date input to receive date
+

requirements.txt

@@ -5,4 +5,4 @@ datasets==2.12.0
 numpy==1.22.4
 pandas==1.5.3
 scikit-learn==1.2.2
-transformers==4.28.1
+transformers==4.28.1