Class PaLM2TextEmbeddingGenerator (1.3.0) 

PaLM2TextEmbeddingGenerator(
    *,
    model_name: typing.Literal[
        "textembedding-gecko", "textembedding-gecko-multilingual"
    ] = "textembedding-gecko",
    version: typing.Optional[str] = None,
    session: typing.Optional[bigframes.session.Session] = None,
    connection_name: typing.Optional[str] = None
)

PaLM2 text embedding generator LLM model.

Parameters
Name Description
model_name str, Default to "textembedding-gecko"

The model for text embedding. “textembedding-gecko” returns model embeddings for text inputs. "textembedding-gecko-multilingual" returns model embeddings for text inputs which support over 100 languages Default to "textembedding-gecko".
version str or None

Model version. Accepted values are "001", "002", "003", "latest" etc. Will use the default version if unset. See https://cloud.google.com/vertex-ai/docs/generative-ai/learn/model-versioning for details.
session bigframes.Session or None

BQ session to create the model. If None, use the global default session.
connection_name str or None

connection to connect with remote service. str of the format <PROJECT_NUMBER/PROJECT_ID>.

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]
) -> bigframes.dataframe.DataFrame

Predict the result from input DataFrame.

Parameter
Name Description
X bigframes.dataframe.DataFrame or bigframes.series.Series

Input DataFrame, which needs to contain a column with name "content". Only the column will be used as input. Content can include preamble, questions, suggestions, instructions, or examples.
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.PaLM2TextEmbeddingGenerator

Save the model to BigQuery.

Parameters
Name Description
model_name str

the name of the model.
replace bool, default False

Determine whether to replace if the model already exists. Default to False.
Returns
Type Description
PaLM2TextEmbeddingGenerator saved model.