copyright | lastupdated | subcollection | ||
---|---|---|---|---|
|
2022-08-02 |
natural-language-understanding |
{:shortdesc: .shortdesc} {:external: target="_blank" .external} {:tip: .tip} {:note: .note} {:beta: .beta} {:pre: .pre} {:important: .important} {:codeblock: .codeblock} {:screen: .screen} {:javascript: .ph data-hd-programlang='javascript'} {:java: .ph data-hd-programlang='java'} {:python: .ph data-hd-programlang='python'} {:swift: .ph data-hd-programlang='swift'}
{: #customizing}
You can extend {{site.data.keyword.nlushort}} with custom models for supported feature and language combinations. {: shortdesc}
{: #customizing-before-you-begin}
- If you haven't done so already, get started with {{site.data.keyword.nlushort}}.
- Check Language support for custom models to make sure that the custom model you want to create is supported.
- Follow the customization instructions for one of the following features.
{: #language-support-for-custom-models}
Check the Custom model support columns in the tables on the Language support page to see the features that support custom models for each language.
{: #training-for-custom-models}
As part of the request to create or update a custom model, you may optionally include a training parameters object that specifies attributes of the model. For details, see feature-specific Classifications training parameters.
{: #targeted-sentiment-for-custom-entities}
For English only, you can get sentiment scores for each custom model entity that is detected by the service by setting the sentiment: true
option in the entities object. No other languages support targeted sentiment for custom model entities.
{: #usage-restrictions-for-custom-models}
The maximum number of models that can be trained via the {{site.data.keyword.nlushort}} customization API in parallel is 3.