From b02ad8045bcec91ac8c234e3cb6c42f93e3a115e Mon Sep 17 00:00:00 2001
From: Ines Montani <ines@ines.io>
Date: Thu, 3 Sep 2020 10:10:13 +0200
Subject: [PATCH] Update docs [ci skip]

---
 website/docs/usage/training.md | 9 +++------
 1 file changed, 3 insertions(+), 6 deletions(-)

diff --git a/website/docs/usage/training.md b/website/docs/usage/training.md
index 43e1193ab..2fabd3f7d 100644
--- a/website/docs/usage/training.md
+++ b/website/docs/usage/training.md
@@ -377,7 +377,8 @@ A **model architecture** is a function that wires up a Thinc
 component or as a layer of a larger network. You can use Thinc as a thin
 [wrapper around frameworks](https://thinc.ai/docs/usage-frameworks) such as
 PyTorch, TensorFlow or MXNet, or you can implement your logic in Thinc
-[directly](https://thinc.ai/docs/usage-models).
+[directly](https://thinc.ai/docs/usage-models). For more details and examples,
+see the usage guide on [layers and architectures](/usage/layers-architectures).
 
 spaCy's built-in components will never construct their `Model` instances
 themselves, so you won't have to subclass the component to change its model
@@ -395,8 +396,6 @@ different tasks. For example:
 | [TransitionBasedParser](/api/architectures#TransitionBasedParser) | Build a [transition-based parser](https://explosion.ai/blog/parsing-english-in-python) model used in the default [`EntityRecognizer`](/api/entityrecognizer) and [`DependencyParser`](/api/dependencyparser). ~~Model[List[Docs], List[List[Floats2d]]]~~ |
 | [TextCatEnsemble](/api/architectures#TextCatEnsemble)             | Stacked ensemble of a bag-of-words model and a neural network model with an internal CNN embedding layer. Used in the default [`TextCategorizer`](/api/textcategorizer). ~~Model[List[Doc], Floats2d]~~                                                   |
 
-<!-- TODO: link to not yet existing usage page on custom architectures etc. -->
-
 ### Metrics, training output and weighted scores {#metrics}
 
 When you train a model using the [`spacy train`](/api/cli#train) command, you'll
@@ -474,11 +473,9 @@ Each custom function can have any numbers of arguments that are passed in via
 the [config](#config), just the built-in functions. If your function defines
 **default argument values**, spaCy is able to auto-fill your config when you run
 [`init fill-config`](/api/cli#init-fill-config). If you want to make sure that a
-given parameter is always explicitely set in the config, avoid setting a default
+given parameter is always explicitly set in the config, avoid setting a default
 value for it.
 
-<!-- TODO: possibly link to new (not yet created) page on creating models ? -->
-
 ### Training with custom code {#custom-code}
 
 > #### Example