21-12-13

app.py

@@ -25,7 +25,7 @@ BART: 60 sec 정도
 Pegasus: 
 
 '''
-plms =["facebook/bart-large-cnn", "google/pegasus-xsum", "t5-base" ]
+plms =["facebook/bart-large-cnn", "google/pegasus-xsum", "t5-small" ]
 
 
 st.write("Information")
@@ -33,7 +33,6 @@ st.write("__Inputs__: Text your input article!!")
 st.write("__Outputs__: Summarizing output text by State-of-the-art NLP summarization Models! ")
 
 
-
 def load_plms(model_name):
     #model_name = "google/pegasus-xsum"
     summarizer = pipeline(task="summarization", model=model_name) 
@@ -58,7 +57,9 @@ with st.spinner('Loading Pretrained Models (_please allow for 30 seconds_)...'):
     summarizer_1 = load_plms(plms[0])   
     summarizer_2 = load_plms(plms[1])   
     summarizer_3 = load_plms(plms[2])   
-    
+    classifier = pipeline("zero-shot-classification",
+                         model="facebook/bart-large-mnli")
+ 
 
 with st.form(key="input_area"):
     display_text = ARTICLE + "\n\n" 
@@ -72,13 +73,13 @@ output_text = []
 if submit_button:
     with st.spinner('On summarizing !...wait a second please..'):
         output_text.append(get_summarizer(summarizer_1, text_input, 150, 5))
-        #output_text.append(get_summarizer(summarizer_2, text_input, 150, 5))
+        output_text.append(get_summarizer(summarizer_2, text_input, 150, 5))
         #output_text.append(get_summarizer(summarizer_3, text_input, 150, 5))
    
     
     st.markdown("### Outputs are here !:  ")
     
-    for i in range(1):
+    for i in range(2):
         st.markdown("**"+ plms[i] +"s Output:  **  ")
         st.text(output_text[i])
         st.success(f"{i+1} of 3 are done!")