Update app.py

app.py

@@ -108,7 +108,6 @@ def main():
     for page in reader.pages:
       text = page.extract_text()
       text_list.append(text)
-      st.write('PDF pages read')
   else:
      st.error("Please upload your own PDF to be analyzed")
      st.stop()
@@ -118,20 +117,20 @@ def main():
   
   sentences = nltk.sent_tokenize(text_list_final)
 
-  st.write('tokeznization completed')
   result =[]
   for i in sentences:
     result1 = i.lower()
     result2 = re.sub(r'[^\w\s]','',result1)
     result.append(result2)
 
-  print("--- %s seconds ---" % (time.time() - start_time))
+  st.write("--- %s seconds ---" % (time.time() - start_time))
   tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased") #bert-base-uncased
   
   model_path = "checkpoint-2850"
   
   model = AutoModelForSequenceClassification.from_pretrained(model_path,id2label={0:'non-causal',1:'causal'})
 
+  st.write('base sequence classification loaded')
   pipe1 = pipeline("text-classification", model=model,tokenizer=tokenizer)
   for sent in result:
     pred = pipe1(sent)