Update app.py

app.py

@@ -33,14 +33,14 @@ def t5_summarize(text):
     return summary
 
 #BART
-# def bart_summarize(text):
-#     tokenizer = BartTokenizer.from_pretrained("facebook/bart-large-cnn")
-#     model = BartForConditionalGeneration.from_pretrained("facebook/bart-large-cnn")
+def bart_summarize(text):
+    tokenizer = BartTokenizer.from_pretrained("facebook/bart-large-cnn")
+    model = BartForConditionalGeneration.from_pretrained("facebook/bart-large-cnn")
 
-#     inputs = tokenizer([text], max_length=1024, return_tensors="pt", truncation=True)
-#     summary_ids = model.generate(inputs["input_ids"], num_beams=4, max_length=150, early_stopping=True)
-#     summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
-#     return summary
+    inputs = tokenizer([text], max_length=1024, return_tensors="pt", truncation=True)
+    summary_ids = model.generate(inputs["input_ids"], num_beams=4, max_length=150, early_stopping=True)
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+    return summary
 
 #Encoder-Decoder
 # def encoder_decoder(text):
@@ -55,7 +55,12 @@ def t5_summarize(text):
 
 #st.write("Generated Summaries are: ")
 # l=transform_summarize(text)
-l=t5_summarize(text)
-st.write(l)
+T5=t5_summarize(text)
+B= bart_summarize(text)
+st.title("Generated Summaries are:")
+st.write("T5")
+st.write(T5)
+st.write("BART")
+st.write(B)
 # print(bart_summarize(text))
 # print(encoder_decoder(text))