I think you would need to modify your current state dict and reload it in your model.
An alternative approach would be:
model = nn.Sequential(
    nn.Conv2d(3, 6, 3, 1, 1),
    nn.BatchNorm2d(6)
)

for child in model.children():
    if isinstance(child, nn.BatchNorm2d):
        with torch.no_grad():
            child.bias = nn.Parameter(torch.empty(6).uniform_())