You can yse torch.randn() and then scale the generated random numbers to match the desired stdded. torch.randn will generated Gaussian Normal Distribution (mean=0, and stddev=1), so by scaling them with 0.1 you can adjust the stddev.
>>> x = torch.randn(10000)
>>> x.std()
tensor(1.0039)
>>> x2 = x / 10
>>> x2.std()
tensor(0.1004)