Hi,
just call torch.nn.init.normal with the parameters:
l = torch.nn.Linear(5,10)
torch.nn.init.normal(l.weight)
torch.nn.init.normal(l.bias)

there are extra arguments for mean and standard deviation.
If all parameters look the same to you, you could do
for p in l.parameters():
    torch.nn.init.normal(p)

though it might not necessarily be a good idea.
Note that there are methods like xavier_normal 50
and kaiming_normal 68 that attempt to set the standard variance based on the number of parameters and, if you provide one, the gain 6 of the activation function.
Best regards
Thomas