# Why do people import weights for DenseNet when Keras includes them?

In several Kaggle kernels I've seen that people often import their weights into Keras' DenseNet. In the following case, I believe the weights are sourced from this github repo and contain the pre-trained weights on the ImageNet dataset.

densenet = DenseNet121(
weights='../input/densenet-keras/DenseNet-BC-121-32-no-top.h5',
include_top=False,
input_shape=(im_size,im_size,3)
)


Why do people load weights from a file when you can use the ImageNet weights within Keras by specifying weights='imagenet' in the following manner?

keras.applications.densenet.DenseNet121(include_top=True, weights='imagenet', input_tensor=None, input_shape=None, pooling=None, classes=1000)


Is there a difference that I should be aware of or is it simply a matter of personal preference?