diff --git a/tools/export_model.py b/tools/export_model.py
index 5d6b338dbcd7071ccda93471c6f9531246927eeb..299bac564e3563fd77c9be7021bb21abfcbe6441 100644
--- a/tools/export_model.py
+++ b/tools/export_model.py
@@ -37,15 +37,17 @@ def parse_args():
     parser.add_argument("--class_dim", type=int, default=1000)
     parser.add_argument("--load_static_weights", type=str2bool, default=False)
     parser.add_argument("--img_size", type=int, default=224)
+    parser.add_argument("--multilabel", type=str2bool, default=False)
 
     return parser.parse_args()
 
 
 class Net(paddle.nn.Layer):
-    def __init__(self, net, class_dim, model):
+    def __init__(self, net, class_dim, model, multilabel):
         super(Net, self).__init__()
         self.pre_net = net(class_dim=class_dim)
         self.model = model
+        self.multilabel = multilabel
 
     def eval(self):
         self.training = False
@@ -57,7 +59,7 @@ class Net(paddle.nn.Layer):
         x = self.pre_net(inputs)
         if self.model == "GoogLeNet":
             x = x[0]
-        x = F.softmax(x)
+        x = F.softmax(x) if not self.multilabel else F.sigmoid(x)
         return x
 
 
@@ -65,7 +67,7 @@ def main():
     args = parse_args()
 
     net = architectures.__dict__[args.model]
-    model = Net(net, args.class_dim, args.model)
+    model = Net(net, args.class_dim, args.model, args.multilabel)
     load_dygraph_pretrain(
         model.pre_net,
         path=args.pretrained_model,