You could print the modules via print(self.effnet) and look for the first conv layer in the model.
Once you’ve found it, e.g. as
(conv1): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)

you could replace it using the attribute name:
self.effnet.conv1 = nn.Conv2d(6, 64, 7, 2, 3, bias=False)

to change the number of input channels to 6.
(Note that I have used a ResNet to show the workflow, so the layer name might differ in your case.)