Update app.py

app.py

@@ -12,6 +12,7 @@ device = 'cuda:0'
 model_v1, tokenizer_v1 = None, None
 model_path_v1 = r'ssocean/NAIP'
 
+@spaces.GPU(duration=60, enable_queue=True)
 def predict_v1(title, abstract):
     global model_v1, tokenizer_v1
     if model_v1 is None:
@@ -37,6 +38,7 @@ def predict_v1(title, abstract):
 scorer_v2 = None
 model_path_v2 = r'ssocean/NAIPv2'
 
+@spaces.GPU(duration=60, enable_queue=True)
 class PaperScorer:
     def __init__(self, model_path: str, device: str = 'cuda', max_length: int = 512):
         self.device = torch.device(device if torch.cuda.is_available() else 'cpu')
@@ -75,8 +77,7 @@ def predict_v2(title, abstract):
     return scorer_v2.score(title, abstract)
 
 
-# ===== 统一接口 =====
-@spaces.GPU(duration=60, enable_queue=True)
+
 def predict(title, abstract, model_version):
     title = title.replace("\n", " ").strip().replace('’', "'")
     abstract = abstract.replace("\n", " ").strip().replace('’', "'")
@@ -97,7 +98,7 @@ def predict(title, abstract, model_version):
         return score
 
 
-# ===== 输入校验 =====
+
 def validate_input(title, abstract):
     title = title.replace("\n", " ").strip().replace('’', "'")
     abstract = abstract.replace("\n", " ").strip().replace('’', "'")
@@ -127,7 +128,7 @@ def update_button_status(title, abstract):
     return gr.update(value=message), gr.update(interactive=True)
 
 
-# ===== 示例数据 =====
+
 examples = [
     [
         "SARDet-100K: Towards Open-Source Benchmark and ToolKit for Large-Scale SAR Object Detection",