Embedding

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This feature has the following limitations:

• Must be enabled by Tecton Support.
• Available for Rift-based Feature Views.

If you would like to participate in the preview, please file a feature request.

Summary

The Embedding class describes an embedding feature that is applied to a Batch via features param.

Example

from tecton import Embedding, batch_feature_view
from tecton.types import String


@batch_feature_view(
    # ...
    features=[
        Embedding(
            column="my_column",
            column_dtype=String,
            model="sentence-transformers/all-MiniLM-L6-v2",
            name="my_embedding_feature",
        ),
    ],
)
def my_fv(data_source):
    pass

Methods

__init__(...)

Parameters

• column (str) – The name of the column to be embedded.
• column_dtype (SdkDataType) - The data type of the column being embedded.
• model (str) - The model name that is used to compute the embedding feature. Check Supported Models section for all supported models.
• name (Optional[str]) – The name of this feature, e.g. my_embedding_feature. Defaults to an autogenerated name.