How to generate high dimensional Gaussian vectors via quasi-mont carlo (QCM) techniques in numpy

i would like to generate a set of gaussian vectors of mean m and covariance C in bumpy, the standard approach is

samplings_set = np.zeros((n,m.size))
for i in range(n):
    vect = np.random.multivariate_normal(m,C)
    vect.shape = (1,m.size)
    samplings_set[i,:] = vect

can i generate the ensemble via quasi-mont carlo (QCM) techniques in numpy? (in order to get a more representative samplings set)