Связаться с намиПопробовать бесплатно
Создавайте контент и получайте гранты!Готовы написать своё руководство? Участвуйте в контент-программе и получайте гранты на работу с облачными сервисами!
Подробнее о программе
Проект Яндекса
© 2026 ТОО «Облачные Сервисы Казахстан»

Domain

Статья создана
Обновлена 28 января 2026 г.

class yandex_ai_studio_sdk._models.text_embeddings.function.AsyncTextEmbeddings

A class for text embeddings models.

It provides the functionality to call a text embeddings model either by a well-known name or a full URI.

__call__(model_name, *, model_version='latest')

Call the specified model for text embeddings. It returns an instance of the specified type of the model.

This method constructs the URI for the model based on the provided name and version. If the name contains ://, it is treated as a full URI. Otherwise, it looks up the model name in the well-known names dictionary. But after this, in any case, we construct a URI in the form emb://<folder_id>//.

Parameters

  • model_name (str) – the name or URI of the model to call.
  • model_version (str) – the version of the model to use. Defaults to ‘latest’.

Return type

ModelTypeT

Model

class yandex_ai_studio_sdk._models.text_embeddings.model.AsyncTextEmbeddingsModel

A class for text embeddings models, providing configuration, request creation, and execution functionalities.

async run(text, *, timeout=60, dimensions=Undefined)

Run the model to generate text embeddings.

Parameters

  • text (str) – the input text for which embeddings are to be generated.
  • timeout – the timeout, or the maximum time to wait for the request to complete in seconds. Defaults to 60 seconds.
  • dimensions (int | Undefined) – the dimensions of output vector

Return type

TextEmbeddingsModelResult

async tune_deferred(train_datasets, *, embeddings_tune_type, validation_datasets=Undefined, name=Undefined, description=Undefined, labels=Undefined, seed=Undefined, lr=Undefined, n_samples=Undefined, additional_arguments=Undefined, dimensions=Undefined, tuning_type=Undefined, scheduler=Undefined, optimizer=Undefined, timeout=60)

Initiate a deferred tuning process for the model.

Parameters

Return type

AsyncTuningTask[AsyncTextEmbeddingsModel]

async tune(train_datasets, *, embeddings_tune_type, validation_datasets=Undefined, name=Undefined, description=Undefined, labels=Undefined, seed=Undefined, lr=Undefined, n_samples=Undefined, additional_arguments=Undefined, dimensions=Undefined, tuning_type=Undefined, scheduler=Undefined, optimizer=Undefined, timeout=60, poll_timeout=259200, poll_interval=60)

Tune the model with the specified training datasets and parameters.

Parameters

Return type

Self

async attach_tune_deferred(task_id, *, timeout=60)

Attach a deferred tuning task using its task ID.

Parameters

  • task_id (str) – the ID of the deferred tuning task to attach to.
  • timeout (float) – the timeout, or the maximum time to wait for the request to complete in seconds. Defaults to 60 seconds.

Return type

AsyncTuningTask[AsyncTextEmbeddingsModel]

property config: ConfigTypeT

configure(*, dimensions=Undefined)

This method calls the parent class’s configure method and returns the configured model instance.

Parameters

dimensions (int | Undefined) – the dimensions of output vector

Return type

Self

property fine_tuned: bool | None

property name: str | None

property owner: str | None

property uri: str

property version: str | None