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Document different ways to create a pipeline (#10762)

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* Document different ways to create a pipeline: moved up/slightly modified paragraph on pipeline creation.

* Document different ways to create a pipeline: changed Finnish to Ukrainian in example for language without trained pipeline.

* Document different ways to create a pipeline: added explanation of blank pipeline.

* Document different ways to create a pipeline: exchanged Ukrainian with Yoruba.
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Raphael Mitsch 2022-05-06 15:40:59 +02:00 committed by GitHub
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website/docs/usage/models.md
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@ -27,6 +27,35 @@ import QuickstartModels from 'widgets/quickstart-models.js'
<QuickstartModels title="Quickstart" id="quickstart" description="Install a default trained pipeline package, get the code to load it from within spaCy and an example to test it. For more options, see the section on available packages below." />
### Usage note
> If lemmatization rules are available for your language, make sure to install
> spaCy with the `lookups` option, or install
> [`spacy-lookups-data`](https://github.com/explosion/spacy-lookups-data)
> separately in the same environment:
>
> ```bash
> $ pip install -U %%SPACY_PKG_NAME[lookups]%%SPACY_PKG_FLAGS
> ```
If a trained pipeline is available for a language, you can download it using the
[`spacy download`](/api/cli#download) command as shown above. In order to use
languages that don't yet come with a trained pipeline, you have to import them
directly, or use [`spacy.blank`](/api/top-level#spacy.blank):
```python
from spacy.lang.yo import Yoruba
nlp = Yoruba() # use directly
nlp = spacy.blank("yo") # blank instance
```
A blank pipeline is typically just a tokenizer. You might want to create a blank
pipeline when you only need a tokenizer, when you want to add more components
from scratch, or for testing purposes. Initializing the language object directly
yields the same result as generating it using `spacy.blank()`. In both cases the
default configuration for the chosen language is loaded, and no pretrained
components will be available.
## Language support {#languages}
spaCy currently provides support for the following languages. You can help by
@ -37,28 +66,6 @@ contribute to development. Also see the
[training documentation](/usage/training) for how to train your own pipelines on
your data.
> #### Usage note
>
> If a trained pipeline is available for a language, you can download it using
> the [`spacy download`](/api/cli#download) command. In order to use languages
> that don't yet come with a trained pipeline, you have to import them directly,
> or use [`spacy.blank`](/api/top-level#spacy.blank):
>
> ```python
> from spacy.lang.fi import Finnish
> nlp = Finnish() # use directly
> nlp = spacy.blank("fi") # blank instance
> ```
>
> If lemmatization rules are available for your language, make sure to install
> spaCy with the `lookups` option, or install
> [`spacy-lookups-data`](https://github.com/explosion/spacy-lookups-data)
> separately in the same environment:
>
> ```bash
> $ pip install -U %%SPACY_PKG_NAME[lookups]%%SPACY_PKG_FLAGS
> ```
import Languages from 'widgets/languages.js'
<Languages />