Generative AI
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Components to leverage native Generative AI capabilities on Data Warehouses.
Description
This components calls function in BigQuery for each row on the input table.
Inputs
Model [FQN]
: The path for the model to be used in the format project_id.dataset.model
Prompt column
: The column in the input source used to generate the prompt.
Max Output Tokens
: an INT64
value in the range [1,1024]
that sets the maximum number of tokens that the model outputs. Specify a lower value for shorter responses and a higher value for longer responses. The default is 50
.
Temperature
: a FLOAT64
value in the range [0.0,1.0]
that is used for sampling during the response generation, which occurs when top_k
and top_p
are applied. It controls the degree of randomness in token selection. Lower temperature
values are good for prompts that require a more deterministic and less open-ended or creative response, while higher temperature
values can lead to more diverse or creative results. A temperature
value of 0
is deterministic, meaning that the highest probability response is always selected. The default is 1.0
.
Top P
: an INT64
value in the range [1,40]
that changes how the model selects tokens for output. Specify a lower value for less random responses and a higher value for more random responses. The default is 40
.
Top K
: a FLOAT64
value in the range [0.0,1.0]
that changes how the model selects tokens for output. Specify a lower value for less random responses and a higher value for more random responses. The default is 1.0
.
Tokens are selected from the most (based on the top_k
value) to least probable until the sum of their probabilities equals the top_p
value. For example, if tokens A, B, and C have a probability of 0.3
, 0.2
, and 0.1
and the top_p
value is 0.5
, then the model selects either A or B as the next token by using the temperature
value and doesn't consider C.
Outputs
Result table [Table]
External links