Compute log likelihood after fitting the GLM?

I am playing around with a toy general linear model (GLM) with MATLAB glmfit.

X=[1;2;3;4];
y=[1.1;2.2;3.5;4.9];
[b, dev, stats] = glmfit(X, y);

How should I compute the log likelihood of the data? I want to do

y_fit = glmval(b, X, 'identity');
ll = nansum(log(normpdf(y, y_fit, sigma)));

But how to find sigma, the standard deviation of the Gaussian?