Interface TuningJob

A tuning job.

interface TuningJob {
    baseModel?: string;
    createTime?: string;
    customBaseModel?: string;
    description?: string;
    encryptionSpec?: EncryptionSpec;
    endTime?: string;
    error?: GoogleRpcStatus;
    experiment?: string;
    labels?: Record<string, string>;
    name?: string;
    outputUri?: string;
    partnerModelTuningSpec?: PartnerModelTuningSpec;
    pipelineJob?: string;
    preferenceOptimizationSpec?: PreferenceOptimizationSpec;
    preTunedModel?: PreTunedModel;
    sdkHttpResponse?: HttpResponse;
    serviceAccount?: string;
    startTime?: string;
    state?: JobState;
    supervisedTuningSpec?: SupervisedTuningSpec;
    tunedModel?: TunedModel;
    tunedModelDisplayName?: string;
    tuningDataStats?: TuningDataStats;
    updateTime?: string;
    veoTuningSpec?: VeoTuningSpec;
}

Properties

baseModel? createTime? customBaseModel? description? encryptionSpec? endTime? error? experiment? labels? name? outputUri? partnerModelTuningSpec? pipelineJob? preferenceOptimizationSpec? preTunedModel? sdkHttpResponse? serviceAccount? startTime? state? supervisedTuningSpec? tunedModel? tunedModelDisplayName? tuningDataStats? updateTime? veoTuningSpec?

Properties

OptionalbaseModel

baseModel?: string

The base model that is being tuned. See Supported models.

OptionalcreateTime

createTime?: string

Output only. Time when the TuningJob was created.

OptionalcustomBaseModel

customBaseModel?: string

Optional. The user-provided path to custom model weights. Set this field to tune a custom model. The path must be a Cloud Storage directory that contains the model weights in .safetensors format along with associated model metadata files. If this field is set, the base_model field must still be set to indicate which base model the custom model is derived from. This feature is only available for open source models.

Optionaldescription

description?: string

Optional. The description of the TuningJob.

OptionalencryptionSpec

encryptionSpec?: EncryptionSpec

Customer-managed encryption key options for a TuningJob. If this is set, then all resources created by the TuningJob will be encrypted with the provided encryption key.

OptionalendTime

endTime?: string

Output only. Time when the TuningJob entered any of the following JobStates: JOB_STATE_SUCCEEDED, JOB_STATE_FAILED, JOB_STATE_CANCELLED, JOB_STATE_EXPIRED.

Optionalerror

error?: GoogleRpcStatus

Output only. Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

Optionalexperiment

experiment?: string

Output only. The Experiment associated with this TuningJob.

Optionallabels

labels?: Record<string, string>

Optional. The labels with user-defined metadata to organize TuningJob and generated resources such as Model and Endpoint. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

Optionalname

name?: string

Output only. Identifier. Resource name of a TuningJob. Format: projects/{project}/locations/{location}/tuningJobs/{tuning_job}

OptionaloutputUri

outputUri?: string

Optional. Cloud Storage path to the directory where tuning job outputs are written to. This field is only available and required for open source models.

OptionalpartnerModelTuningSpec

partnerModelTuningSpec?: PartnerModelTuningSpec

Tuning Spec for open sourced and third party Partner models.

OptionalpipelineJob

pipelineJob?: string

Output only. The resource name of the PipelineJob associated with the TuningJob. Format: projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}.

OptionalpreferenceOptimizationSpec

preferenceOptimizationSpec?: PreferenceOptimizationSpec

Tuning Spec for Preference Optimization.

OptionalpreTunedModel

preTunedModel?: PreTunedModel

The pre-tuned model for continuous tuning.

OptionalsdkHttpResponse

sdkHttpResponse?: HttpResponse

Used to retain the full HTTP response.

OptionalserviceAccount

serviceAccount?: string

The service account that the tuningJob workload runs as. If not specified, the Vertex AI Secure Fine-Tuned Service Agent in the project will be used. See https://cloud.google.com/iam/docs/service-agents#vertex-ai-secure-fine-tuning-service-agent Users starting the pipeline must have the iam.serviceAccounts.actAs permission on this service account.

OptionalstartTime

startTime?: string

Output only. Time when the TuningJob for the first time entered the JOB_STATE_RUNNING state.

Optionalstate

state?: JobState

Output only. The detailed state of the job.

OptionalsupervisedTuningSpec

supervisedTuningSpec?: SupervisedTuningSpec

Tuning Spec for Supervised Fine Tuning.

OptionaltunedModel

tunedModel?: TunedModel

Output only. The tuned model resources associated with this TuningJob.

OptionaltunedModelDisplayName

tunedModelDisplayName?: string

Optional. The display name of the TunedModel. The name can be up to 128 characters long and can consist of any UTF-8 characters. For continuous tuning, tuned_model_display_name will by default use the same display name as the pre-tuned model. If a new display name is provided, the tuning job will create a new model instead of a new version.

OptionaltuningDataStats

tuningDataStats?: TuningDataStats

Output only. The tuning data statistics associated with this TuningJob.

OptionalupdateTime

updateTime?: string

Output only. Time when the TuningJob was most recently updated.

OptionalveoTuningSpec

veoTuningSpec?: VeoTuningSpec

Tuning Spec for Veo Tuning.

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Properties