Update app.py

app.py

@@ -4,11 +4,7 @@ import pandas as pd
 
 from transformers import pipeline
 
-# model_name="aminghias/distilbert-base-uncased-finetuned-imdb"
 
-# mask_filler = pipeline(
-#     "fill-mask", model=model_name
-# )
 
 pipe = pipeline("fill-mask", model="aminghias/Clinical-BERT-finetuned")
 pipe2 = pipeline("fill-mask", model="emilyalsentzer/Bio_ClinicalBERT")
@@ -16,8 +12,6 @@ pipe3= pipeline("fill-mask", model="medicalai/ClinicalBERT")
 
 
 
-
-
 def predict(text):
 
     pred1 = pipe(text)
@@ -48,36 +42,27 @@ def predict(text):
     
     df_join=df_join.sort_values(by='score_average',ascending=False)
     df_join=df_join.reset_index(drop=True)
-    # df_join=df_join.dropna()
-    # df_join=df_join.fillna(0)
+
     df=df_join.copy()
     df_join=df_join[['token_str','score_average','score_finetuned_CBERT','score_Bio_CBERT','score_CBERT']].head()
 
-    # gr.Interface(fn=lambda: df_join, inputs=None, outputs=gr.Dataframe(headers=df_join.columns)).launch()
-    
-    # print(df_join)
-    # df_join['sum_sequence'][0]
+
     return (df['sum_sequence'][0],df_join)
 
-    
-  # return (pipe(text)[0]['sequence'],pipe2(text)[0]['sequence'])
+
     
 demo = gr.Interface(
   fn=predict, 
   inputs='text',
   # outputs='text',
   outputs=['text', gr.Dataframe()],
-    # outputs='text','text',
-
-     # outputs=gr.Dataframe(headers=['title', 'author', 'text']), allow_flagging='never')
 
   title="Filling Missing Clinical/Medical Data ",
     examples=[ ['The  high blood pressure was due to [MASK]  which is critical.'],
               ['The  patient is suffering from throat infection causing [MASK] and cough.']
              ],
     description="This application fills any missing words in the medical domain",
-  # fn=lambda: df, inputs=None, outputs=gr.Dataframe(headers=df_join.columns)
- # fn = infer, inputs = inputs, outputs = outputs, examples = [[df_join.head()]]
+
 )
 
 demo.launch()