diff --git a/docs/src/using-turing/interface.md b/docs/src/using-turing/interface.md
index 24e999953a..868f4ca8b6 100644
--- a/docs/src/using-turing/interface.md
+++ b/docs/src/using-turing/interface.md
@@ -100,9 +100,6 @@ Note that we only have to do this because we are not yet integrating the sampler
 struct DensityModel{F<:Function} <: AbstractModel
     ℓπ :: F
 end
-
-# Default density constructor.
-DensityModel(π::Function, data::T) where T = DensityModel{VariateForm, ValueSupport, T}(π, data)
 ```
 
 ### Transition
@@ -118,7 +115,7 @@ struct Transition{T<:Union{Vector{<:Real}, <:Real}, L<:Real} <: AbstractTransiti
 end
 
 # Store the new draw and its log density.
-Transition(model::M, θ::T) where {M<:DensityModel, T} = Transition(θ, ℓπ(model, θ))
+Transition(model::DensityModel, θ) = Transition(θ, ℓπ(model, θ))
 ```
 
 `Transition` can now store any type of parameter, whether it's a vector of draws from multiple parameters or a single univariate draw. We should also tell the interface what specific subtype of `AbstractTransition` we're going to use, so we can just define a new method on `transition_type`:
@@ -198,7 +195,7 @@ q(spl::MetropolisHastings, θ::Vector{<:Real}, θcond::Vector{<:Real}) = logpdf(
 q(spl::MetropolisHastings, t1::Transition, t2::Transition) = q(spl, t1.θ, t2.θ)
 
 # Calculate the density of the model given some parameterization.
-ℓπ(model::DensityModel, θ::T) where T = model.ℓπ(θ)
+ℓπ(model::DensityModel, θ) = model.ℓπ(θ)
 ℓπ(model::DensityModel, t::Transition) = t.lp
 
 # Define the other step function. Returns a Transition containing
@@ -235,13 +232,13 @@ The last piece in our puzzle is a `bundle_samples` function, which accepts a `Ve
 # A basic chains constructor that works with the Transition struct we defined.
 function bundle_samples(
     rng::AbstractRNG, 
-    ℓ::DensityModel, 
+    ℓ::AbstractModel, 
     s::MetropolisHastings, 
     N::Integer, 
-    ts::Vector{T}; 
+    ts::Vector{<:AbstractTransition}; 
     param_names=missing,
     kwargs...
-) where {ModelType<:AbstractModel, T<:AbstractTransition}
+)
     # Turn all the transitions into a vector-of-vectors.
     vals = copy(reduce(hcat,[vcat(t.θ, t.lp) for t in ts])')