Upload app.py

app.py

@@ -12,7 +12,7 @@ from heapq import nlargest
 import warnings
 from sklearn.feature_extraction.text import TfidfVectorizer
 import numpy as np
-from transformers import PegasusForConditionalGeneration, PegasusTokenizer
+#from transformers import PegasusForConditionalGeneration, PegasusTokenizer
 
 warnings.filterwarnings("ignore")
 
@@ -20,7 +20,7 @@ def get_wiki_original_text(inp):
     text = wikipedia.summary(inp)
     return text
 
-
+"""
 def  get_wiki_summary_by_pegasus(inp):
     text = wikipedia.summary(inp)
     tokenizer = PegasusTokenizer.from_pretrained('google/pegasus-xsum')
@@ -28,7 +28,7 @@ def  get_wiki_summary_by_pegasus(inp):
     model = PegasusForConditionalGeneration.from_pretrained("google/pegasus-xsum")
     summary = model.generate(**tokens)
     return tokenizer.decode(summary)
-    
+"""    
 
 
 def get_wiki_summary_by_lem(inp):
@@ -89,7 +89,7 @@ sample = [['Europe'], ['Great Depression'], ['Crocodile Dundee']]
 
 iface = Parallel(gr.Interface(fn=get_wiki_original_text, inputs=gr.inputs.Textbox(label="Requested Topic from Wikipedia    :   "), outputs="text"),
                  gr.Interface(fn=get_wiki_summary_by_lem, inputs=gr.inputs.Textbox(label="Requested Topic from Wikipedia    :   "), outputs="text"),
-                 gr.Interface(fn=get_wiki_summary_by_pegasus, inputs=gr.inputs.Textbox(label="Requested Topic from Wikipedia    :   "), outputs="text"),
+                 #gr.Interface(fn=get_wiki_summary_by_pegasus, inputs=gr.inputs.Textbox(label="Requested Topic from Wikipedia    :   "), outputs="text"),