Interface CfnFlow.PromptModelInferenceConfigurationProperty
- All Superinterfaces:
software.amazon.jsii.JsiiSerializable
- All Known Implementing Classes:
CfnFlow.PromptModelInferenceConfigurationProperty.Jsii$Proxy
- Enclosing class:
CfnFlow
@Stability(Stable)
public static interface CfnFlow.PromptModelInferenceConfigurationProperty
extends software.amazon.jsii.JsiiSerializable
Contains inference configurations related to model inference for a prompt.
For more information, see Inference parameters .
Example:
// The code below shows an example of how to instantiate this type. // The values are placeholders you should change. import software.amazon.awscdk.services.bedrock.*; PromptModelInferenceConfigurationProperty promptModelInferenceConfigurationProperty = PromptModelInferenceConfigurationProperty.builder() .maxTokens(123) .stopSequences(List.of("stopSequences")) .temperature(123) .topP(123) .build();
- See Also:
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Nested Class Summary
Modifier and TypeInterfaceDescriptionstatic final class
A builder forCfnFlow.PromptModelInferenceConfigurationProperty
static final class
An implementation forCfnFlow.PromptModelInferenceConfigurationProperty
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Method Summary
Modifier and TypeMethodDescriptionbuilder()
default Number
The maximum number of tokens to return in the response.A list of strings that define sequences after which the model will stop generating.default Number
Controls the randomness of the response.default Number
getTopP()
The percentage of most-likely candidates that the model considers for the next token.Methods inherited from interface software.amazon.jsii.JsiiSerializable
$jsii$toJson
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Method Details
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getMaxTokens
The maximum number of tokens to return in the response.- See Also:
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getStopSequences
A list of strings that define sequences after which the model will stop generating.- See Also:
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getTemperature
Controls the randomness of the response.Choose a lower value for more predictable outputs and a higher value for more surprising outputs.
- See Also:
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getTopP
The percentage of most-likely candidates that the model considers for the next token.- See Also:
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builder
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