Update docs [ci skip]

website/docs/usage/layers-architectures.md

@@ -6,6 +6,7 @@ menu:
   - ['Defining Sublayers', 'sublayers']
   - ['PyTorch & TensorFlow', 'frameworks']
   - ['Trainable Components', 'components']
+next: /usage/projects
 ---
 
 ​ A **model architecture** is a function that wires up a
@@ -44,7 +45,7 @@ are: ​
 
 The model type-signatures help you figure out which model architectures and
 components can fit together. For instance, the
-[`TextCategorizer`](/api/textcaregorizer) class expects a model typed
+[`TextCategorizer`](/api/textcategorizer) class expects a model typed
 ~~Model[List[Doc], Floats2d]~~, because the model will predict one row of
 category probabilities per `Doc`. In contrast, the `Tagger` class expects a
 model typed ~~Model[List[Doc], List[Floats2d]]~~, because it needs to predict

website/docs/usage/training.md

@@ -1,6 +1,6 @@
 ---
 title: Training Models
-next: /usage/projects
+next: /usage/layers-architectures
 menu:
   - ['Introduction', 'basics']
   - ['Quickstart', 'quickstart']

website/docs/usage/v3.md

@@ -292,7 +292,9 @@ format for documenting argument and return types.
 <Infobox title="New or reworked documentation" emoji="📖" list>
 
 - **Usage: ** [Embeddings & Transformers](/usage/embeddings-transformers),
-  [Training models](/usage/training), [Projects](/usage/projects),
+  [Training models](/usage/training),
+  [Layers & Architectures](/usage/layers-architectures),
+  [Projects](/usage/projects),
   [Custom pipeline components](/usage/processing-pipelines#custom-components),
   [Custom tokenizers](/usage/linguistic-features#custom-tokenizer)
 - **API Reference: ** [Library architecture](/api),

website/meta/sidebars.json

@@ -26,7 +26,7 @@
                     { "text": "Training Models", "url": "/usage/training", "tag": "new" },
                     {
                         "text": "Layers & Model Architectures",
-                        "url": "/usage/architectures",
+                        "url": "/usage/layers-architectures",
                         "tag": "new"
                     },
                     { "text": "spaCy Projects", "url": "/usage/projects", "tag": "new" },