- Categories:
String & binary functions (Large Language Model)
EMBED_TEXT_1024 (SNOWFLAKE.CORTEX)¶
Creates a vector embedding of 1024 dimensions from text.
Syntax¶
SNOWFLAKE.CORTEX.EMBED_TEXT_1024( <model>, <text> )
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-l-v2.0
nv-embed-qa-4
multilingual-e5-large
voyage-multilingual-2
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. See Required privileges for more information on granting this privilege.
Example¶
In this example, a vector embedding is generated for the phrase hello world
using the snowflake-arctic-embed-l-v2.0
model:
SELECT SNOWFLAKE.CORTEX.EMBED_TEXT_1024('snowflake-arctic-embed-l-v2.0', 'hello world');
In this example, a vector embedding is generated for the Spanish phrase hola mundo
using the snowflake-arctic-embed-l-v2.0
model:
SELECT SNOWFLAKE.CORTEX.EMBED_TEXT_1024('snowflake-arctic-embed-l-v2.0', 'hola mundo');
Legal notices¶
Refer to Snowflake AI and ML.