elasticsearch-js/docs/reference/api/MlTrainedModelConfig.md

Interface MlTrainedModelConfig

Name	Type	Description
compressed_definition	string
create_time	DateTime	The time when the trained model was created.
created_by	string	Information on the creator of the trained model.
default_field_map	Record<string, string>	Any field map described in the inference configuration takes precedence.
description	string	The free-text description of the trained model.
estimated_heap_memory_usage_bytes	integer	The estimated heap usage in bytes to keep the trained model in memory.
estimated_operations	integer	The estimated number of operations to use the trained model.
fully_defined	boolean	True if the full model definition is present.
inference_config	MlInferenceConfigCreateContainer	The default configuration for inference. This can be either a regression, classification, or one of the many NLP focused configurations. It must match the underlying definition.trained_model's target_type. For pre-packaged models such as ELSER the config is not required.
input	MlTrainedModelConfigInput	The input field names for the model definition.
license_level	string	The license level of the trained model.
location	MlTrainedModelLocation
metadata	MlTrainedModelConfigMetadata	An object containing metadata about the trained model. For example, models created by data frame analytics contain analysis_config and input objects.
model_id	Id	Identifier for the trained model.
model_package	MlModelPackageConfig
model_size_bytes	ByteSize
model_type	MlTrainedModelType	The model type
platform_architecture	string
prefix_strings	MlTrainedModelPrefixStrings
tags	string[]	A comma delimited string of tags. A trained model can have many tags, or none.
version	VersionString	The Elasticsearch version number in which the trained model was created.