[[reference-ml-put_trained_model]]

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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.putTrainedModel

Create a trained model. Enable you to supply a trained model that is not created by data frame analytics.

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

[discrete]
==== Function signature

[source,ts]
----
(MlPutTrainedModelRequest, options?): Promise<MlPutTrainedModelResponse>
----

[discrete]
===== `MlPutTrainedModelRequest`

[source,ts]
----
interface MlPutTrainedModelRequest extends <<shared-type-request-base, RequestBase>> {
  model_id: <<shared-type-id, Id>>
  defer_definition_decompression?: boolean
  wait_for_completion?: boolean
  compressed_definition?: string
  definition?: MlPutTrainedModelDefinition
  description?: string
  inference_config?: MlInferenceConfigCreateContainer
  input?: MlPutTrainedModelInput
  metadata?: any
  model_type?: MlTrainedModelType
  model_size_bytes?: <<shared-type-long, long>>
  platform_architecture?: string
  tags?: string[]
  prefix_strings?: MlTrainedModelPrefixStrings
}
----

[discrete]
===== `MlPutTrainedModelResponse`

[source,ts]
----
type MlPutTrainedModelResponse = MlTrainedModelConfig
----