Categories:: String & binary functions (Large Language Model)

EMBED_TEXT_768 (SNOWFLAKE.CORTEX)¶

Note

AI_EMBED is the latest version of this function. Use AI_EMBED for the latest functionality. You can continue to use EMBED_TEXT_768 (SNOWFLAKE.CORTEX).

Creates a vector embedding of 768 dimensions from English-language text.

Syntax¶

SNOWFLAKE.CORTEX.EMBED_TEXT_768( <model>, <text> )

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Arguments¶

model

A string specifying the vector embedding model to be used to generate the embedding. This must be one of the following values.

snowflake-arctic-embed-m-v1.5

snowflake-arctic-embed-m

e5-base-v2

Supported models might have different costs.

text

The text for which an embedding should be calculated.

Returns¶

A vector embedding of type VECTOR.

Access control requirements¶

You must use a role that has been granted the SNOWFLAKE.CORTEX_USER database role. For more information about granting this privilege, see Required privileges.

Examples¶

In this example, a vector embedding is generated for the phrase hello world using the snowflake-arctic-embed-m-v1.5 model:

SELECT SNOWFLAKE.CORTEX.EMBED_TEXT_768('snowflake-arctic-embed-m-v1.5', 'hello world');

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Legal notices¶

Refer to Snowflake AI and ML.

Limitations¶

Snowflake Cortex functions do not support dynamic tables.