The input to the convolution layer must be a 4-dimensional tesnor with the following dimensions:   [batch_size, channels, width, height].
So, if you have a single example, and a single channel, that means your input should be of size [1, 1, 14, 14]. So, all you need to do is to reshape your input to fit the dimensionality requirement using one of the following ways:
# using reshape:
>>> x = x.reshape(1, 1, 14, 14)

# or using view():
>>> x = x.view(1, 1, 14, 14)

>>> x.shape
torch.Size([1, 1, 14, 14])

Then, pass this input to your model.