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remove set_morphology from docs
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@ -21,16 +21,12 @@ architectures and their arguments and hyperparameters.
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>
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> ```python
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> from spacy.pipeline.tagger import DEFAULT_TAGGER_MODEL
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> config = {
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> "set_morphology": False,
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> "model": DEFAULT_TAGGER_MODEL,
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> }
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> config = {"model": DEFAULT_TAGGER_MODEL}
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> nlp.add_pipe("tagger", config=config)
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> ```
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| Setting | Description |
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| ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
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| `set_morphology` | Whether to set morphological features. Defaults to `False`. ~~bool~~ |
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| `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]]~~ |
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```python
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@ -63,8 +59,6 @@ shortcut for this and instantiate the component using its string name and
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| `vocab` | The shared vocabulary. ~~Vocab~~ |
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| `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]]~~ |
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| `name` | String name of the component instance. Used to add entries to the `losses` during training. ~~str~~ |
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| _keyword-only_ | |
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| `set_morphology` | Whether to set morphological features. ~~bool~~ |
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## Tagger.\_\_call\_\_ {#call tag="method"}
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