Class _TunableModelMixin (1.33.1)

_TunableModelMixin(model_id: str, endpoint_name: typing.Optional[str] = None)

Model that can be tuned.

Methods

_TunableModelMixin

_TunableModelMixin(model_id: str, endpoint_name: typing.Optional[str] = None)

Creates a LanguageModel.

This constructor should not be called directly. Use LanguageModel.from_pretrained(model_name=...) instead.

get_tuned_model

get_tuned_model(
    tuned_model_name: str,
) -> vertexai.language_models._language_models._LanguageModel

Loads the specified tuned language model.

list_tuned_model_names

list_tuned_model_names() -> typing.Sequence[str]

Lists the names of tuned models.

tune_model

tune_model(
    training_data: typing.Union[str, pandas.core.frame.DataFrame],
    *,
    train_steps: typing.Optional[int] = None,
    learning_rate: typing.Optional[float] = None,
    learning_rate_multiplier: typing.Optional[float] = None,
    tuning_job_location: typing.Optional[str] = None,
    tuned_model_location: typing.Optional[str] = None,
    model_display_name: typing.Optional[str] = None,
    tuning_evaluation_spec: typing.Optional[TuningEvaluationSpec] = None,
    default_context: typing.Optional[str] = None
) -> _LanguageModelTuningJob

Tunes a model based on training data.

This method launches and returns an asynchronous model tuning job. Usage:

tuning_job = model.tune_model(...)
... do some other work
tuned_model = tuning_job.get_tuned_model()  # Blocks until tuning is complete

Exceptions
Type	Description
`ValueError`	If the "tuning_job_location" value is not supported
`ValueError`	If the "tuned_model_location" value is not supported
`RuntimeError`	If the model does not support tuning