update app file

app.py

@@ -7,12 +7,16 @@ tokenizer = PreTrainedTokenizerFast.from_pretrained(model_name)
 model = BartForConditionalGeneration.from_pretrained(model_name)
 
 def process_paragraph(paragraph):
-    input_ids = tokenizer.encode(paragraph, return_tensors='pt', max_length=1024)
+    # Return a list from tokenizer.encode instead of tensor
+    input_ids_list = tokenizer.encode(paragraph, max_length=1024)
+    # Convert the list to tensor when needed
+    input_ids = torch.tensor([input_ids_list])
+    
     output = model.generate(input_ids, max_length=32, num_beams=10, early_stopping=True)
     subheading = tokenizer.decode(output[0], skip_special_tokens=True)
 
     subheading_final = ""  # 실제 반환할 소제목
-    check_list = ["em class", "violet_text", "green_text", "red_text","blue_text"]
+    check_list = ["em class", "violet_text", "green_text", "red_text", "blue_text"]
     if  subheading=="O" or "OO" in subheading:
         subheading_final = "😢소제목 생성 실패: 더 자세한 내용이 필요합니다." 
     elif any(x in subheading for x in check_list):