Problems fitting a hurdle model using glmmADMB

I've explored my data some more and have an update to the above message. I
think my model for the non-zero counts is underfitting because the
zero-truncated negative binomial distribution is not a great representation
of the data. My count data for y>0 are as following:

summary(as.factor(dat.nz$Count))

 1   2   3   4   5   6   7   8  10  11  12
172  39  18  14   4   8   2   1   1   1   1

The zero-truncated negative binomial family does not seem to fit for this
many ones and the corresponding drop-off to lower values. Thus, I suppose I
shouldn't use this family of models for the 2nd part of the hurdle model
that I'm trying to fit. But what are the alternatives? I have thought about
quantile regression and am searching for non-parametric methods, but I am
not sure if it is acceptable to split up the model in this way.