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.

Method: publishers.models.computeTokens

Return a list of tokens based on the input text.

Endpoint

post


                https://{service-endpoint}/v1/{endpoint}:computeTokens

Where {service-endpoint} is one of the supported service endpoints.

Path parameters

endpoint string

Required. The name of the Endpoint requested to get lists of tokens and token ids.

Request body

The request body contains data with the following structure:

Fields

instances[] value (Value format)

Optional. The instances that are the input to token computing API call. Schema is identical to the prediction schema of the text model, even for the non-text models, like chat models, or Codey models.

model string

Optional. The name of the publisher model requested to serve the prediction. Format: projects/{project}/locations/{location}/publishers/*/models/*

contents[] object (Content)

Optional. Input content.

Response body

If successful, the response body contains an instance of ComputeTokensResponse.