Weighting the fit on the errors can cause large problems if the errors are wrong, so TelFit is now doing an un-weighted fit. Additionally, the bounds implementation is much better; they are implemented in the same way as with lmfit (http://lmfit.github.io/lmfit-py/bounds.html)
Going back to the default values for ftol and xtol in scipy.optimize.leastsq
SVD broadening is a little bit safer.