I would like to fit a generalized ordered logit model to some data I have. I first tried to use the ordered logit model using the MASS package from R, but it seems that the proportional odds assumption is violated by the data. Indeed, not all independent variables do exert the same effect across all categories of the dependent variable. Hence I am a bit blocked. I say that I could use the generalized ordered logit model instead, but could not find how to use it. Indeed, I can not find any package on either R or python that coud help me on that. 
If someone has any hints on packages I could use, it would be of great help!
Thank you very much!
Try the 'VGAM' package. There is a function called vglm.
example: vglm(Var2~factor(Var1),cumulative(parallel = F),data) generalized order model
cumulative(parallel=T) will perform a proportional odds model.
parallel=F is the default.
generalized ordered logit in R or python