[[reference-ml-get_trained_models_stats]]

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||        ██████╗ ███████╗ █████╗ ██████╗ ███╗   ███╗███████╗                                                            ||
||        ██╔══██╗██╔════╝██╔══██╗██╔══██╗████╗ ████║██╔════╝                                                            ||
||        ██████╔╝█████╗  ███████║██║  ██║██╔████╔██║█████╗                                                              ||
||        ██╔══██╗██╔══╝  ██╔══██║██║  ██║██║╚██╔╝██║██╔══╝                                                              ||
||        ██║  ██║███████╗██║  ██║██████╔╝██║ ╚═╝ ██║███████╗                                                            ||
||        ╚═╝  ╚═╝╚══════╝╚═╝  ╚═╝╚═════╝ ╚═╝     ╚═╝╚══════╝                                                            ||
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||    This file is autogenerated, DO NOT send pull requests that changes this file directly.                             ||
||    You should update the script that does the generation, which can be found in:                                      ||
||    https://github.com/elastic/elastic-client-generator-js                                                             ||
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||    You can run the script with the following command:                                                                 ||
||       npm run elasticsearch -- --version <version>                                                                    ||
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[discrete]
[[client.ml.getTrainedModelsStats]]
=== client.ml.getTrainedModelsStats

Get trained models usage info. You can get usage information for multiple trained models in a single API request by using a list of model IDs or a wildcard expression.

{ref}/get-trained-models-stats.html[{es} documentation]

[discrete]
==== Function signature

[source,ts]
----
(MlGetTrainedModelsStatsRequest, options?): Promise<MlGetTrainedModelsStatsResponse>
----

[discrete]
==== Request

[pass]
++++
<pre>
++++
interface MlGetTrainedModelsStatsRequest extends <<RequestBase>> {
  model_id?: <<Ids>>
  allow_no_match?: boolean
  from?: <<integer>>
  size?: <<integer>>
}

[pass]
++++
</pre>
++++
[discrete]
==== Response

[pass]
++++
<pre>
++++
interface MlGetTrainedModelsStatsResponse {
  count: <<integer>>
  trained_model_stats: <<MlTrainedModelStats>>[]
}

[pass]
++++
</pre>
++++
