Class MultimodalEmbeddingGenerator (2.29.0)

Version latest

• 2.29.0 (latest)
• 2.28.0
• 2.27.0
• 2.26.0
• 2.25.0
• 2.24.0
• 2.23.0
• 2.22.0
• 2.21.0
• 2.20.0
• 2.19.0
• 2.18.0
• 2.17.0
• 2.16.0
• 2.15.0
• 2.14.0
• 2.13.0
• 2.12.0
• 2.11.0
• 2.10.0
• 2.9.0
• 2.8.0
• 2.7.0
• 2.6.0
• 2.5.0
• 2.4.0
• 2.3.0
• 2.2.0
• 1.36.0
• 1.35.0
• 1.34.0
• 1.33.0
• 1.32.0
• 1.31.0
• 1.30.0
• 1.29.0
• 1.28.0
• 1.27.0
• 1.26.0
• 1.25.0
• 1.24.0
• 1.22.0
• 1.21.0
• 1.20.0
• 1.19.0
• 1.18.0
• 1.17.0
• 1.16.0
• 1.15.0
• 1.14.0
• 1.13.0
• 1.12.0
• 1.11.1
• 1.10.0
• 1.9.0
• 1.8.0
• 1.7.0
• 1.6.0
• 1.5.0
• 1.4.0
• 1.3.0
• 1.2.0
• 1.1.0
• 1.0.0
• 0.26.0
• 0.25.0
• 0.24.0
• 0.23.0
• 0.22.0
• 0.21.0
• 0.20.1
• 0.19.2
• 0.18.0
• 0.17.0
• 0.16.0
• 0.15.0
• 0.14.1
• 0.13.0
• 0.12.0
• 0.11.0
• 0.10.0
• 0.9.0
• 0.8.0
• 0.7.0
• 0.6.0
• 0.5.0
• 0.4.0
• 0.3.0
• 0.2.0

MultimodalEmbeddingGenerator(
    *,
    model_name: typing.Optional[typing.Literal["multimodalembedding@001"]] = None,
    session: typing.Optional[bigframes.session.Session] = None,
    connection_name: typing.Optional[str] = None
)

Multimodal embedding generator LLM model.

Note: BigFrames Blob is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the Service Specific Terms(https://cloud.google.com/terms/service-terms#1). Pre-GA products and features are available "as is" and might have limited support. For more information, see the launch stage descriptions (https://cloud.google.com/products#product-launch-stages).

Methods

__repr__

__repr__()

Print the estimator's constructor with all non-default parameter values.

get_params

get_params(deep: bool = True) -> typing.Dict[str, typing.Any]

Get parameters for this estimator.

Parameter
Name	Description
deep	bool, default True Default True. If True, will return the parameters for this estimator and contained subobjects that are estimators.

Returns
Type	Description
Dictionary	A dictionary of parameter names mapped to their values.

predict

predict(
    X: typing.Union[
        bigframes.dataframe.DataFrame,
        bigframes.series.Series,
        pandas.core.frame.DataFrame,
        pandas.core.series.Series,
    ],
    *,
    max_retries: int = 0
) -> bigframes.dataframe.DataFrame

Predict the result from input DataFrame.

Returns
Type	Description
bigframes.dataframe.DataFrame	DataFrame of shape (n_samples, n_input_columns + n_prediction_columns). Returns predicted values.

to_gbq

to_gbq(
    model_name: str, replace: bool = False
) -> bigframes.ml.llm.MultimodalEmbeddingGenerator

Save the model to BigQuery.

Returns
Type	Description
MultimodalEmbeddingGenerator	Saved model.