Try Gemini 1.5 models, the latest multimodal models in Vertex AI, and see what you can build with up to a 2M token context window. Try Gemini 1.5 models, the latest multimodal models in Vertex AI, and see what you can build with up to a 2M token context window.

Module sft (1.67.1)

Classes for supervised tuning.

Classes

SupervisedTuningJob

SupervisedTuningJob(tuning_job_name: str)

Initializes class with project, location, and api_client.

Parameters
Name	Description
`project`	`str` Project of the resource noun.
`location`	`str` The location of the resource noun.
`credentials`	`google.auth.credentials.Credentials` Optional custom credentials to use when accessing interacting with resource noun.
`resource_name`	`str` A fully-qualified resource name or ID.

Modules Functions

train

train(
    *,
    source_model: typing.Union[str, vertexai.generative_models.GenerativeModel],
    train_dataset: str,
    validation_dataset: typing.Optional[str] = None,
    tuned_model_display_name: typing.Optional[str] = None,
    epochs: typing.Optional[int] = None,
    learning_rate_multiplier: typing.Optional[float] = None,
    adapter_size: typing.Optional[typing.Literal[1, 4, 8, 16]] = None,
    labels: typing.Optional[typing.Dict[str, str]] = None
) -> vertexai.tuning._supervised_tuning.SupervisedTuningJob

Tunes a model using supervised training.

Parameter
Name	Description
`source_model`	`str` Model name for tuning, e.g., "gemini-1.0-pro-002".