Update API docs

website/docs/api/architectures.md

@@ -4,4 +4,34 @@ teaser: Pre-defined model architectures included with the core library
 source: spacy/ml/models
 ---
 
-TODO: write
+TODO: intro and how architectures work, link to
+[`registry`](/api/top-level#registry),
+[custom models](/usage/training#custom-models) usage etc.
+
+## Parser architectures {source="spacy/ml/models/parser.py"}
+
+### spacy.TransitionBasedParser.v1
+
+<!-- TODO: intro -->
+
+> #### Example Config
+>
+> ```ini
+> [model]
+> @architectures = "spacy.TransitionBasedParser.v1"
+> nr_feature_tokens = 6
+> hidden_width = 64
+> maxout_pieces = 2
+>
+> [model.tok2vec]
+> # ...
+> ```
+
+| Name                | Type                                       | Description |
+| ------------------- | ------------------------------------------ | ----------- |
+| `tok2vec`           | [`Model`](https://thinc.ai/docs/api-model) |             |
+| `nr_feature_tokens` | int                                        |             |
+| `hidden_width`      | int                                        |             |
+| `maxout_pieces`     | int                                        |             |
+| `use_upper`         | bool                                       |             |
+| `nO`                | int                                        |             |

website/docs/api/dependencyparser.md

@@ -8,6 +8,18 @@ This class is a subclass of `Pipe` and follows the same API. The pipeline
 component is available in the [processing pipeline](/usage/processing-pipelines)
 via the ID `"parser"`.
 
+## Default config {#config}
+
+This is the default configuration used to initialize the model powering the
+pipeline component. See the [model architectures](/api/architectures)
+documentation for details on the architectures and their arguments and
+hyperparameters. To learn more about how to customize the config and train
+custom models, check out the [training config](/usage/training#config) docs.
+
+```python
+https://github.com/explosion/spaCy/blob/develop/spacy/pipeline/defaults/parser_defaults.cfg
+```
+
 ## DependencyParser.\_\_init\_\_ {#init tag="method"}
 
 > #### Example

website/docs/api/entitylinker.md

@@ -12,6 +12,18 @@ This class is a subclass of `Pipe` and follows the same API. The pipeline
 component is available in the [processing pipeline](/usage/processing-pipelines)
 via the ID `"entity_linker"`.
 
+## Default config {#config}
+
+This is the default configuration used to initialize the model powering the
+pipeline component. See the [model architectures](/api/architectures)
+documentation for details on the architectures and their arguments and
+hyperparameters. To learn more about how to customize the config and train
+custom models, check out the [training config](/usage/training#config) docs.
+
+```python
+https://github.com/explosion/spaCy/blob/develop/spacy/pipeline/defaults/entity_linker_defaults.cfg
+```
+
 ## EntityLinker.\_\_init\_\_ {#init tag="method"}
 
 > #### Example

website/docs/api/entityrecognizer.md

@@ -8,6 +8,18 @@ This class is a subclass of `Pipe` and follows the same API. The pipeline
 component is available in the [processing pipeline](/usage/processing-pipelines)
 via the ID `"ner"`.
 
+## Default config {#config}
+
+This is the default configuration used to initialize the model powering the
+pipeline component. See the [model architectures](/api/architectures)
+documentation for details on the architectures and their arguments and
+hyperparameters. To learn more about how to customize the config and train
+custom models, check out the [training config](/usage/training#config) docs.
+
+```python
+https://github.com/explosion/spaCy/blob/develop/spacy/pipeline/defaults/ner_defaults.cfg
+```
+
 ## EntityRecognizer.\_\_init\_\_ {#init tag="method"}
 
 > #### Example

website/docs/api/morphologizer.md

@@ -0,0 +1,23 @@
+---
+title: Morphologizer
+tag: class
+source: spacy/pipeline/morphologizer.pyx
+new: 3
+---
+
+A trainable pipeline component to predict morphological features. This class is
+a subclass of `Pipe` and follows the same API. The component is also available
+via the string name `"morphologizer"`. After initialization, it is typically
+added to the processing pipeline using [`nlp.add_pipe`](/api/language#add_pipe).
+
+## Default config {#config}
+
+This is the default configuration used to initialize the model powering the
+pipeline component. See the [model architectures](/api/architectures)
+documentation for details on the architectures and their arguments and
+hyperparameters. To learn more about how to customize the config and train
+custom models, check out the [training config](/usage/training#config) docs.
+
+```python
+https://github.com/explosion/spaCy/blob/develop/spacy/pipeline/defaults/morphologizer_defaults.cfg
+```

website/docs/api/sentencerecognizer.md

@@ -11,6 +11,18 @@ subclass of `Pipe` and follows the same API. The component is also available via
 the string name `"senter"`. After initialization, it is typically added to the
 processing pipeline using [`nlp.add_pipe`](/api/language#add_pipe).
 
+## Default config {#config}
+
+This is the default configuration used to initialize the model powering the
+pipeline component. See the [model architectures](/api/architectures)
+documentation for details on the architectures and their arguments and
+hyperparameters. To learn more about how to customize the config and train
+custom models, check out the [training config](/usage/training#config) docs.
+
+```python
+https://github.com/explosion/spaCy/blob/develop/spacy/pipeline/defaults/senter_defaults.cfg
+```
+
 ## SentenceRecognizer.\_\_init\_\_ {#init tag="method"}
 
 Initialize the sentence recognizer.

website/docs/api/textcategorizer.md

@@ -9,6 +9,20 @@ This class is a subclass of `Pipe` and follows the same API. The pipeline
 component is available in the [processing pipeline](/usage/processing-pipelines)
 via the ID `"textcat"`.
 
+## Default config {#config}
+
+This is the default configuration used to initialize the model powering the
+pipeline component. See the [model architectures](/api/architectures)
+documentation for details on the architectures and their arguments and
+hyperparameters. To learn more about how to customize the config and train
+custom models, check out the [training config](/usage/training#config) docs.
+
+```python
+https://github.com/explosion/spaCy/blob/develop/spacy/pipeline/defaults/textcat_defaults.cfg
+```
+
+<!-- TODO: do we also need to document the other defaults here? -->
+
 ## TextCategorizer.\_\_init\_\_ {#init tag="method"}
 
 > #### Example

website/docs/api/tok2vec.md

@@ -0,0 +1,19 @@
+---
+title: Tok2Vec
+source: spacy/pipeline/tok2vec.py
+new: 3
+---
+
+TODO: document
+
+## Default config {#config}
+
+This is the default configuration used to initialize the model powering the
+pipeline component. See the [model architectures](/api/architectures)
+documentation for details on the architectures and their arguments and
+hyperparameters. To learn more about how to customize the config and train
+custom models, check out the [training config](/usage/training#config) docs.
+
+```python
+https://github.com/explosion/spaCy/blob/develop/spacy/pipeline/defaults/tok2vec_defaults.cfg
+```

website/meta/sidebars.json

@@ -79,7 +79,9 @@
                 "items": [
                     { "text": "Language", "url": "/api/language" },
                     { "text": "Tokenizer", "url": "/api/tokenizer" },
+                    { "text": "Tok2Vec", "url": "/api/tok2vec" },
                     { "text": "Lemmatizer", "url": "/api/lemmatizer" },
+                    { "text": "Morphologizer", "url": "/api/morphologizer" },
                     { "text": "Tagger", "url": "/api/tagger" },
                     { "text": "DependencyParser", "url": "/api/dependencyparser" },
                     { "text": "EntityRecognizer", "url": "/api/entityrecognizer" },