The number is the input number to the next backward function, so can only be non-zero when a function has multiple differentiable outputs (there aren’t that many, but e.g. the RNN functions typically do).
A minimal example that doesn’t serve much purpose except showing you a 1 is:
a, b = torch.randn(2, requires_grad=True).unbind()
c = a+b
print(c.grad_fn.next_functions)

Unbind is not that well-known, it is the “opposite” of stack, splitting a tensor along one (the first by default) dimension into a list.
Best regards
Thomas