diff --git a/models/export.py b/models/export.py
index 06d51f29e2e4..b262df83bf21 100644
--- a/models/export.py
+++ b/models/export.py
@@ -28,6 +28,9 @@
     attempt_download(opt.weights)
     model = torch.load(opt.weights, map_location=torch.device('cpu'))['model'].float()
     model.eval()
+    model.fuse()
+
+    # Update model
     model.model[-1].export = True  # set Detect() layer export=True
     y = model(img)  # dry run
 
@@ -47,7 +50,6 @@
 
         print('\nStarting ONNX export with onnx %s...' % onnx.__version__)
         f = opt.weights.replace('.pt', '.onnx')  # filename
-        model.fuse()  # only for ONNX
         torch.onnx.export(model, img, f, verbose=False, opset_version=12, input_names=['images'],
                           output_names=['classes', 'boxes'] if y is None else ['output'])
 
diff --git a/models/yolo.py b/models/yolo.py
index bba015a80a7e..f1c3c3f9084a 100644
--- a/models/yolo.py
+++ b/models/yolo.py
@@ -163,7 +163,7 @@ def fuse(self):  # fuse model Conv2d() + BatchNorm2d() layers
             if type(m) is Conv:
                 m._non_persistent_buffers_set = set()  # pytorch 1.6.0 compatability
                 m.conv = fuse_conv_and_bn(m.conv, m.bn)  # update conv
-                m.bn = None  # remove batchnorm
+                delattr(m, 'bn')  # remove batchnorm
                 m.forward = m.fuseforward  # update forward
         self.info()
         return self