OpenSearch/docs/java-rest/high-level/ml/put-trained-model.asciidoc

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--
:api: put-trained-model
:request: PutTrainedModelRequest
:response: PutTrainedModelResponse
--
[role="xpack"]
[id="{upid}-{api}"]
=== Put trained models API
experimental:[]
experimental::[]
Creates a new trained model for inference.
The API accepts a +{request}+ object as a request and returns a +{response}+.
[id="{upid}-{api}-request"]
==== Put trained models request
A +{request}+ requires the following argument:
["source","java",subs="attributes,callouts,macros"]
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include-tagged::{doc-tests-file}[{api}-request]
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<1> The configuration of the {infer} trained model to create
[id="{upid}-{api}-config"]
==== Trained model configuration
The `TrainedModelConfig` object contains all the details about the trained model
configuration and contains the following arguments:
["source","java",subs="attributes,callouts,macros"]
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include-tagged::{doc-tests-file}[{api}-config]
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<1> The {infer} definition for the model
<2> Optionally, if the {infer} definition is large, you may choose to compress it for transport.
Do not supply both the compressed and uncompressed definitions.
<3> The unique model id
<4> The input field names for the model definition
<5> Optionally, a human-readable description
<6> Optionally, an object map contain metadata about the model
<7> Optionally, an array of tags to organize the model
<8> The default inference config to use with the model. Must match the underlying
definition target_type.
include::../execution.asciidoc[]
[id="{upid}-{api}-response"]
==== Response
The returned +{response}+ contains the newly created trained model.
The +{response}+ will omit the model definition as a precaution against
streaming large model definitions back to the client.
["source","java",subs="attributes,callouts,macros"]
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include-tagged::{doc-tests-file}[{api}-response]
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