try that

README.md

@@ -6,9 +6,9 @@ This is meant to be a simple, unambitious package that provides basic, user-frie
 multithreaded calculations via higher-order functions, with a focus on [data parallelism](https://en.wikipedia.org/wiki/Data_parallelism).
 
 It re-exports the very useful function `chunks` from [ChunkSplitters.jl](https://github.com/m3g/ChunkSplitters.jl), and
-provides the following functions
+provides the following functions: 
 
-<details><summary> `tmapreduce` </summary>
+<details><summary> tmapreduce </summary>
 <p>
 
     tmapreduce(f, op, A::AbstractArray;
@@ -46,7 +46,9 @@ needed if you are using a `:static` schedule, since the `:dynamic` schedule is u
 </details>
 </p>
 
-<details><summary>`treducemap`</summary>
+____________________________________
+
+<details><summary> treducemap </summary>
 <p>
 
     treducemap(op, f, A::AbstractArray;
@@ -85,7 +87,9 @@ needed if you are using a `:static` schedule, since the `:dynamic` schedule is u
 </details>
 </p>
 
-<details><summary>`treduce`</summary>
+____________________________________
+
+<details><summary>treduce</summary>
 <p>
 
 
@@ -124,7 +128,7 @@ needed if you are using a `:static` schedule, since the `:dynamic` schedule is u
 </details>
 </p>
 
-<details><summary>`tforeach`</summary>
+<details><summary>tforeach</summary>
 <p>
 
     tforeach(f, A::AbstractArray;
@@ -144,7 +148,9 @@ Apply `f` to each element of `A` on multiple parallel tasks, and return `nothing
 </details>
 </p>
 
-<details><summary>`tmap`</summary>
+____________________________________
+
+<details><summary>tmap</summary>
 <p>
 
 
@@ -166,7 +172,9 @@ A multithreaded function like `Base.map`. Create a new container `similar` to `A
 </details>
 </p>
 
-<details><summary>`tmap!`</summary>
+____________________________________
+
+<details><summary>tmap!</summary>
 <p>
 
     tmap!(f, out, A::AbstractArray;