Shared parameters in multiple models

Interfaces brms
1

I have the following model

  bf(rel_size ~ eta,
     nlf(eta ~  A + K * inv_logit(-exp(slope) *(log10(dose) - gamma) ) ),
     A ~ 0 + insect + (1|qq|experiment),
     K ~ 0 + insect + (1|qq|experiment),
     slope ~ 0 + insect + (1|qq|experiment),
     gamma ~ 0 + insect + offset(delta) + (1|qq|experiment),
     nl = TRUE)

However I have data where dose is 0, which causes gradients to explode. For this particular model the likelihood is well defined as dose → 0 (eta → A + K). When I have written such a model in pure stan (without the grouping effects) I write something like this

...
    // compute non-linear predictor values
    if (dose[n] == 0){
      mu[n] = A + K;
    }else{
      mu[n] = A + K / (1 + exp(  exp(slope) * (log10(dose[n]) - gamma)));
    }
}
...

How would I achieve something similar with brms? One way would be if one could provide multiple models to brms with shared parameters, but I don’t think thats currently possible? Is there any other way?