- 2.30.0 (latest)
- 2.29.0
- 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
GeminiTextGenerator(
*,
model_name: typing.Optional[
typing.Literal[
"gemini-1.5-pro-preview-0514",
"gemini-1.5-flash-preview-0514",
"gemini-1.5-pro-001",
"gemini-1.5-pro-002",
"gemini-1.5-flash-001",
"gemini-1.5-flash-002",
"gemini-2.0-flash-exp",
"gemini-2.0-flash-001",
"gemini-2.0-flash-lite-001",
"gemini-2.5-pro",
"gemini-2.5-flash",
"gemini-2.5-flash-lite",
]
] = None,
session: typing.Optional[bigframes.session.Session] = None,
connection_name: typing.Optional[str] = None,
max_iterations: int = 300
)Gemini text generator LLM model.
Methods
GeminiTextGenerator
GeminiTextGenerator(
*,
model_name: typing.Optional[
typing.Literal[
"gemini-1.5-pro-preview-0514",
"gemini-1.5-flash-preview-0514",
"gemini-1.5-pro-001",
"gemini-1.5-pro-002",
"gemini-1.5-flash-001",
"gemini-1.5-flash-002",
"gemini-2.0-flash-exp",
"gemini-2.0-flash-001",
"gemini-2.0-flash-lite-001",
"gemini-2.5-pro",
"gemini-2.5-flash",
"gemini-2.5-flash-lite",
]
] = None,
session: typing.Optional[bigframes.session.Session] = None,
connection_name: typing.Optional[str] = None,
max_iterations: int = 300
)Gemini text generator LLM model.
__init__
__init__(
*, model_name=None, session=None, connection_name=None, max_iterations=300
)API documentation for __init__ method.
fit
fit(X, y)Fine tune GeminiTextGenerator model. Only support "gemini-1.5-pro-002", "gemini-1.5-flash-002", "gemini-2.0-flash-001", and "gemini-2.0-flash-lite-001"models for now.
| Returns | |
|---|---|
| Type | Description |
GeminiTextGenerator |
Fitted estimator. |
get_params
get_params(deep=True)Get parameters for this estimator.
| Parameter | |
|---|---|
| Name | Description |
deep |
bool, default True
Default |
| Returns | |
|---|---|
| Type | Description |
Dictionary |
A dictionary of parameter names mapped to their values. |
predict
predict(
X,
*,
temperature=0.9,
max_output_tokens=8192,
top_k=40,
top_p=1.0,
ground_with_google_search=False,
max_retries=0,
prompt=None,
output_schema=None
)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. |
score
score(X, y, task_type="text_generation")Calculate evaluation metrics of the model. Only support "gemini-1.5-pro-002", "gemini-1.5-flash-002", "gemini-2.0-flash-lite-001", and "gemini-2.0-flash-001".
Output matches that of the BigQuery ML.EVALUATE function. See: https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-evaluate#remote-model-llm for the outputs relevant to this model type.| Returns | |
|---|---|
| Type | Description |
bigframes.dataframe.DataFrame |
The DataFrame as evaluation result. |
to_gbq
to_gbq(model_name, replace=False)Save the model to BigQuery.
| Returns | |
|---|---|
| Type | Description |
GeminiTextGenerator |
Saved model. |