Class _TunableModelMixin (1.55.0)

Version 1.55.0

• 1.73.0 (latest)
• 1.72.0
• 1.71.1
• 1.70.0
• 1.69.0
• 1.68.0
• 1.67.1
• 1.66.0
• 1.65.0
• 1.63.0
• 1.62.0
• 1.60.0
• 1.59.0
• 1.58.0
• 1.57.0
• 1.56.0
• 1.55.0
• 1.54.1
• 1.53.0
• 1.52.0
• 1.51.0
• 1.50.0
• 1.49.0
• 1.48.0
• 1.47.0
• 1.46.0
• 1.45.0
• 1.44.0
• 1.43.0
• 1.39.0
• 1.38.1
• 1.37.0
• 1.36.4
• 1.35.0
• 1.34.0
• 1.33.1
• 1.32.0
• 1.31.1
• 1.30.1
• 1.29.0
• 1.28.1
• 1.27.1
• 1.26.1
• 1.25.0
• 1.24.1
• 1.23.0
• 1.22.1
• 1.21.0
• 1.20.0
• 1.19.1
• 1.18.3
• 1.17.1
• 1.16.1
• 1.15.1
• 1.14.0
• 1.13.1
• 1.12.1
• 1.11.0
• 1.10.0
• 1.9.0
• 1.8.1
• 1.7.1
• 1.6.2
• 1.5.0
• 1.4.3
• 1.3.0
• 1.2.0
• 1.1.1
• 1.0.1
• 0.9.0
• 0.8.0
• 0.7.1
• 0.6.0
• 0.5.1
• 0.4.0
• 0.3.1

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

Model that can be tuned with supervised fine tuning (SFT).

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.

Parameters
Name	Description
model_id	str Identifier of a Vertex LLM. Example: "text-bison@001"
endpoint_name	typing.Optional[str] Vertex Endpoint resource name for the model

tune_model

tune_model(
    training_data: typing.Union[str, pandas.core.frame.DataFrame],
    *,
    corpus_data: typing.Optional[str] = None,
    queries_data: typing.Optional[str] = None,
    test_data: typing.Optional[str] = None,
    validation_data: typing.Optional[str] = None,
    batch_size: typing.Optional[int] = None,
    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,
    task_type: typing.Optional[str] = None,
    machine_type: typing.Optional[str] = None,
    accelerator: typing.Optional[str] = None,
    accelerator_count: typing.Optional[int] = None,
    accelerator_type: typing.Optional[typing.Literal["TPU", "GPU"]] = None,
    max_context_length: typing.Optional[str] = None,
    output_dimensionality: typing.Optional[int] = 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

Parameter
Name	Description
training_data	typing.Union[str, pandas.core.frame.DataFrame] A URI to training data in TSV (for embedding models), or JSON lines format, or a Pandas DataFrame.

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