Let’s check the source code 4.
def __init__(self, in_features, out_features, bias=True):
    ...
    self.weight = Parameter(torch.Tensor(out_features, in_features))

def reset_parameters(self):
    stdv = 1. / math.sqrt(self.weight.size(1))
    self.weight.data.uniform_(-stdv, stdv)
    ...

So the answer is: a uniform distribution of values between -1/sqrt(in_features) and 1/sqrt(in_features)