diff --git a/src/dims/seq.jl b/src/dims/seq.jl
index 3b0d3d02..58ec76e3 100644
--- a/src/dims/seq.jl
+++ b/src/dims/seq.jl
@@ -17,4 +17,4 @@ convert{T,S}(::Type{Seq{T,S}},storage::S) =
        Juno.trim(collect(b)))
 end
 
-typealias BatchSeq{T<:Seq} Batch{T}
+BatchSeq{T<:Seq} = Batch{T}
diff --git a/src/layers/shape.jl b/src/layers/shape.jl
index 5fe47cd9..20c171cb 100644
--- a/src/layers/shape.jl
+++ b/src/layers/shape.jl
@@ -1,6 +1,6 @@
 export Input
 
-typealias Dims{N} NTuple{N,Int}
+Dims{N} = NTuple{N,Int}
 
 dims(d::Dims) = d
 
diff --git a/src/model.jl b/src/model.jl
index d333d9b2..24b0424b 100644
--- a/src/model.jl
+++ b/src/model.jl
@@ -15,7 +15,7 @@ where `W` and `b` are a trainable matrix and vector of weights repectively. The
 closer to a protocol, and models don't need to inherit from this type. Normal
 Julia functions are models with 0 parameters, for example.
 """
-abstract Model
+abstract type Model end
 
 """
     back!(m::Model, ΔY, X...) => ΔX