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how-to-guides/create-service/create-service.md
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@ -76,7 +76,7 @@ assert type_safe_greeter('Andras').output == 'Hi Andras'
### Using `@parameter`
If you wish to turn of logging or specify custom validation for your parameters, you can use the [@parameter][great_ai.parameter] decorator.
If you wish to turn off logging or specify custom validation for your parameters, you can use the [@parameter][great_ai.parameter] decorator.
!!! note
By default, all parameters that are not affected by an explicit [@parameter][great_ai.parameter] or [@use_model][great_ai.use_model] are automatically decorated with [@parameter][great_ai.parameter] when [@GreatAI.create][great_ai.GreatAI.create] is called.
@ -85,7 +85,7 @@ If you wish to turn of logging or specify custom validation for your parameters,
from great_ai import GreatAI, use_model
@GreatAI.create
@use_model('name_of_my_model', version='latest')
@parameter('your_name', disable_logging=True)
def type_safe_greeter(your_name: str, model) -> str:
return f'Hi {your_name}!'
@ -105,7 +105,7 @@ from great_ai import save_model, GreatAI, parameter, use_model, log_metric
save_model(4, 'secret-number') #(1)
@GreatAI.create
@parameter('positive_number', validator=lambda n: n > 0, disable_logging=True)
@parameter('positive_number', validate=lambda n: n > 0, disable_logging=True)
@use_model('secret-number', version='latest', model_kwarg_name='secret')
def add_number(positive_number: int, secret: int) -> int:
log_metric(