Starting April 29, 2025, Gemini 1.5 Pro and Gemini 1.5 Flash models are not available in projects that have no prior usage of these models, including new projects. For details, see Model versions and lifecycle.
Required. The instances that are the input to the prediction call.
A DeployedModel may have an upper limit on the number of instances it
supports per request, and when it is exceeded the prediction call errors
in case of AutoML Models, or, in case of customer created Models, the
behaviour is as documented by that Model.
The schema of any single instance may be specified via Endpoint's
DeployedModels' Model'sPredictSchemata'sinstance_schema_uri.
Required. The instances that are the input to the prediction call.
A DeployedModel may have an upper limit on the number of instances it
supports per request, and when it is exceeded the prediction call errors
in case of AutoML Models, or, in case of customer created Models, the
behaviour is as documented by that Model.
The schema of any single instance may be specified via Endpoint's
DeployedModels' Model'sPredictSchemata'sinstance_schema_uri.
Required. The instances that are the input to the prediction call.
A DeployedModel may have an upper limit on the number of instances it
supports per request, and when it is exceeded the prediction call errors
in case of AutoML Models, or, in case of customer created Models, the
behaviour is as documented by that Model.
The schema of any single instance may be specified via Endpoint's
DeployedModels' Model'sPredictSchemata'sinstance_schema_uri.
Required. The instances that are the input to the prediction call.
A DeployedModel may have an upper limit on the number of instances it
supports per request, and when it is exceeded the prediction call errors
in case of AutoML Models, or, in case of customer created Models, the
behaviour is as documented by that Model.
The schema of any single instance may be specified via Endpoint's
DeployedModels' Model'sPredictSchemata'sinstance_schema_uri.
Required. The instances that are the input to the prediction call.
A DeployedModel may have an upper limit on the number of instances it
supports per request, and when it is exceeded the prediction call errors
in case of AutoML Models, or, in case of customer created Models, the
behaviour is as documented by that Model.
The schema of any single instance may be specified via Endpoint's
DeployedModels' Model'sPredictSchemata'sinstance_schema_uri.
The parameters that govern the prediction. The schema of the parameters may
be specified via Endpoint's DeployedModels' Model's
PredictSchemata'sparameters_schema_uri.
The parameters that govern the prediction. The schema of the parameters may
be specified via Endpoint's DeployedModels' Model's
PredictSchemata'sparameters_schema_uri.
The parameters that govern the prediction. The schema of the parameters may
be specified via Endpoint's DeployedModels' Model's
PredictSchemata'sparameters_schema_uri.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-04-28 UTC."],[],[]]