diff --git a/docs/src/models/basics.md b/docs/src/models/basics.md
index 06901d99..26c7da76 100644
--- a/docs/src/models/basics.md
+++ b/docs/src/models/basics.md
@@ -32,8 +32,6 @@ julia> gradient(f, [2, 1], [2, 0])
 But machine learning models can have *hundreds* of parameters! To handle this, Flux lets you work with collections of parameters, via `params`. You can get the gradient of all parameters used in a program without explicitly passing them in.
 
 ```jldoctest basics
-julia> using Flux
-
 julia> x = [2, 1];
 
 julia> y = [2, 0];