diff --git a/website/docs/usage/models.md b/website/docs/usage/models.md
index 9b686c947..5e9bd688f 100644
--- a/website/docs/usage/models.md
+++ b/website/docs/usage/models.md
@@ -85,7 +85,8 @@ import the `MultiLanguage` class directly, or call
### Chinese language support {#chinese new=2.3}
-The Chinese language class supports three word segmentation options:
+The Chinese language class supports three word segmentation options, `char`,
+`jieba` and `pkuseg`:
> ```python
> from spacy.lang.zh import Chinese
@@ -95,11 +96,12 @@ The Chinese language class supports three word segmentation options:
>
> # Jieba
> cfg = {"segmenter": "jieba"}
-> nlp = Chinese(meta={"tokenizer": {"config": cfg}})
+> nlp = Chinese.from_config({"nlp": {"tokenizer": cfg}})
>
> # PKUSeg with "default" model provided by pkuseg
-> cfg = {"segmenter": "pkuseg", "pkuseg_model": "default"}
-> nlp = Chinese(meta={"tokenizer": {"config": cfg}})
+> cfg = {"segmenter": "pkuseg"}
+> nlp = Chinese.from_config({"nlp": {"tokenizer": cfg}})
+> nlp.tokenizer.initialize(pkuseg_model="default")
> ```
1. **Character segmentation:** Character segmentation is the default
@@ -116,41 +118,34 @@ The Chinese language class supports three word segmentation options:
In spaCy v3.0, the default Chinese word segmenter has switched from Jieba to
-character segmentation. Also note that
-[`pkuseg`](https://github.com/lancopku/pkuseg-python) doesn't yet ship with
-pre-compiled wheels for Python 3.8. If you're running Python 3.8, you can
-install it from our fork and compile it locally:
-
-```bash
-$ pip install https://github.com/honnibal/pkuseg-python/archive/master.zip
-```
+character segmentation.
-The `meta` argument of the `Chinese` language class supports the following
-following tokenizer config settings:
+The `initialize` method for the Chinese tokenizer class supports the following
+config settings for loading pkuseg models:
-| Name | Description |
-| ------------------ | --------------------------------------------------------------------------------------------------------------- |
-| `segmenter` | Word segmenter: `char`, `jieba` or `pkuseg`. Defaults to `char`. ~~str~~ |
-| `pkuseg_model` | **Required for `pkuseg`:** Name of a model provided by `pkuseg` or the path to a local model directory. ~~str~~ |
-| `pkuseg_user_dict` | Optional path to a file with one word per line which overrides the default `pkuseg` user dictionary. ~~str~~ |
+| Name | Description |
+| ------------------ | ------------------------------------------------------------------------------------------------------------------------------------- |
+| `pkuseg_model` | Name of a model provided by `pkuseg` or the path to a local model directory. ~~str~~ |
+| `pkuseg_user_dict` | Optional path to a file with one word per line which overrides the default `pkuseg` user dictionary. Defaults to `"default"`. ~~str~~ |
```python
### Examples
+# Initialize the pkuseg tokenizer
+cfg = {"segmenter": "pkuseg"}
+nlp = Chinese.from_config({"nlp": {"tokenizer": cfg}})
+
# Load "default" model
-cfg = {"segmenter": "pkuseg", "pkuseg_model": "default"}
-nlp = Chinese(config={"tokenizer": {"config": cfg}})
+nlp.tokenizer.initialize(pkuseg_model="default")
# Load local model
-cfg = {"segmenter": "pkuseg", "pkuseg_model": "/path/to/pkuseg_model"}
-nlp = Chinese(config={"tokenizer": {"config": cfg}})
+nlp.tokenizer.initialize(pkuseg_model="/path/to/pkuseg_model")
# Override the user directory
-cfg = {"segmenter": "pkuseg", "pkuseg_model": "default", "pkuseg_user_dict": "/path"}
-nlp = Chinese(config={"tokenizer": {"config": cfg}})
+nlp.tokenizer.initialize(pkuseg_model="default", pkuseg_user_dict="/path/to/user_dict")
```
You can also modify the user dictionary on-the-fly:
@@ -185,8 +180,11 @@ from spacy.lang.zh import Chinese
# Train pkuseg model
pkuseg.train("train.utf8", "test.utf8", "/path/to/pkuseg_model")
+
# Load pkuseg model in spaCy Chinese tokenizer
-nlp = Chinese(meta={"tokenizer": {"config": {"pkuseg_model": "/path/to/pkuseg_model", "require_pkuseg": True}}})
+cfg = {"segmenter": "pkuseg"}
+nlp = Chinese.from_config({"nlp": {"tokenizer": cfg}})
+nlp.tokenizer.initialize(pkuseg_model="/path/to/pkuseg_model")
```