diff --git a/Project.toml b/Project.toml
index 0a5bcee..78860bd 100644
--- a/Project.toml
+++ b/Project.toml
@@ -2,7 +2,7 @@ name = "RelationalDatasets"
 uuid = "6b8bdb16-f930-11eb-22b5-7ba1dabdf7a8"
 license = "Apache 2.0"
 authors = ["Alexander L. Hayes <alexander@batflyer.net>"]
-version = "0.1.1"
+version = "0.2.0"
 
 [deps]
 HTTP = "cd3eb016-35fb-5094-929b-558a96fad6f3"
diff --git a/README.md b/README.md
index 4c1c7bd..fafc4c9 100644
--- a/README.md
+++ b/README.md
@@ -1,11 +1,13 @@
 # RelationalDatasets.jl
 
-> *A small library for loading and downloading relational datasets.*
->
-> or:
->
-> *The [`relational-datasets`](https://github.com/srlearn/relational-datasets)
-> Python package—but written in Julia.*
+*A small library for loading and downloading relational datasets.*
+
+or: *The [`relational-datasets`](https://github.com/srlearn/relational-datasets)
+Python package—but written in Julia.*
+
+```console
+add RelationalDatasets
+```
 
 ![GitHub release (latest by date)](https://img.shields.io/github/v/release/srlearn/RelationalDatasets.jl)
 ![GitHub](https://img.shields.io/github/license/srlearn/RelationalDatasets.jl)
@@ -14,6 +16,11 @@
 
 ## Usage
 
+[![RelationalDatasets.jl stable documentation](https://img.shields.io/badge/docs-stable-blue.svg)](https://srlearn.github.io/RelationalDatasets.jl/stable)
+[![RelationalDatasets.jl latest documentation](https://img.shields.io/badge/docs-dev-blue.svg)](https://srlearn.github.io/RelationalDatasets.jl/dev)
+
+### Loading and Downloading Benchmark Datasets
+
 `RelationalDatasets.jl` exports a single function: `load` to return train
 and test folds.
 
@@ -21,11 +28,34 @@ and test folds.
 using RelationalDatasets
 
 train, test = load("webkb", "v0.0.4", fold=2)
-
-println(length(train.facts))
+length(train.facts)
 # 1344
 ```
 
+### Converting Vector-based Datasets
+
+*Binary classification when `y` is a vector of 0/1*:
+
+```julia
+using RelationalDatasets
+
+data, modes = RelationalDatasets.from_vector(
+  [0 1 1; 1 0 2; 2 2 0],
+  [0, 0, 1],
+)
+```
+
+*Regression when `y` is a vector of floats*:
+
+```julia
+using RelationalDatasets
+
+data, modes = RelationalDatasets.from_vector(
+  [0 1 1; 1 0 2; 2 2 0],
+  [1.1, 0.9, 2.5],
+)
+```
+
 ## Install
 
 ### From Registry