remove set_morphology from docs
@@ -21,16 +21,12 @@ architectures and their arguments and hyperparameters.
>
> ```python
> from spacy.pipeline.tagger import DEFAULT_TAGGER_MODEL
-> config = {
-> "set_morphology": False,
-> "model": DEFAULT_TAGGER_MODEL,
-> }
+> config = {"model": DEFAULT_TAGGER_MODEL}
> nlp.add_pipe("tagger", config=config)
> ```
| Setting | Description |
| ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
-| `set_morphology` | Whether to set morphological features. Defaults to `False`. ~~bool~~ |
| `model` | A model instance that predicts the tag probabilities. The output vectors should match the number of tags in size, and be normalized as probabilities (all scores between 0 and 1, with the rows summing to `1`). Defaults to [Tagger](/api/architectures#Tagger). ~~Model[List[Doc], List[Floats2d]]~~ |
```python
@@ -63,8 +59,6 @@ shortcut for this and instantiate the component using its string name and
| `vocab` | The shared vocabulary. ~~Vocab~~ |
| `model` | A model instance that predicts the tag probabilities. The output vectors should match the number of tags in size, and be normalized as probabilities (all scores between 0 and 1, with the rows summing to `1`). ~~Model[List[Doc], List[Floats2d]]~~ |
| `name` | String name of the component instance. Used to add entries to the `losses` during training. ~~str~~ |
-| _keyword-only_ | |
-| `set_morphology` | Whether to set morphological features. ~~bool~~ |
## Tagger.\_\_call\_\_ {#call tag="method"}
