Update README

README.md

@@ -4,18 +4,85 @@ Nx-powered Neural Networks
 
 ## Installation
 
-If [available in Hex](https://hex.pm/docs/publish), the package can be installed
-by adding `axon` to your list of dependencies in `mix.exs`:
+In order to use `Axon`, you will need Elixir installed. Then create an Elixir project via the mix build tool:
+
+```
+$ mix new my_app
+```
+
+Then you can add `Axon` as dependency in your `mix.exs`. At the moment you will have to use a Git dependency while we work on our first release:
 
 ```elixir
 def deps do
   [
-    {:axon, "~> 0.1.0"}
+    {:axon, "~> 0.1.0-dev", github: "elixir-nx/axon", branch: "main"}
   ]
 end
 ```
 
-Documentation can be generated with [ExDoc](https://github.com/elixir-lang/ex_doc)
-and published on [HexDocs](https://hexdocs.pm). Once published, the docs can
-be found at [https://hexdocs.pm/axon](https://hexdocs.pm/axon).
+You will typically want to include another `Nx` backend or as a dependency as well:
+
+```elixir
+def deps do
+  [
+    {:axon, "~> 0.1.0-dev", github: "elixir-nx/axon", branch: "main"},
+    {:exla, "~> 0.1.0-dev", github: "elixir-nx/exla", branch: "main", sparse: "exla"},
+    {:torchx, "~> 0.1.0-dev", github: "elixir-nx/nx", sparse: "torchx"},
+  ]
+end
+```
+
+## A Basic Neural Network
+
+You can create neural networks inside modules with the `model` macro:
+
+```elixir
+defmodule MyNN do
+  use Axon
+
+  model do
+    input({nil, 784})
+    |> dense(128)
+    |> relu()
+    |> dense(64, activation: :tanh)
+    |> dropout(rate: 0.5)
+    |> dense(10)
+    |> activation(:softmax)
+  end
+end
+```
+
+`model` will generate the numerical definitions `init_random_params/0` and `predict/2`. You can also name models for using multiple models in the same training loop:
+
+```elixir
+defmodule GAN do
+  use Axon
+
+  model generator do
+    input({nil, 100})
+    |> dense(128)
+    |> tanh()
+    |> dense(256)
+    |> tanh()
+    |> dense(512)
+    |> tanh()
+    |> dense(1024)
+    |> tanh()
+    |> dense(784)
+    |> tanh()
+  end
+
+  model discriminator do
+    input({nil, 28, 28})
+    |> flatten()
+    |> dense(128)
+    |> relu()
+    |> dense(64)
+    |> relu()
+    |> dense(2)
+    |> softmax()
+  end
+end
+```
 
+In the above example, you can initialize and apply both models using: `init_generator`/`generator` and `init_discriminator`/`discriminator` respectively.

mix.exs

@@ -7,7 +7,7 @@ defmodule Axon.MixProject do
   def project do
     [
       app: :axon,
-      version: "0.1.0",
+      version: @version,
       elixir: "~> 1.11",
       start_permanent: Mix.env() == :prod,
       deps: deps(),