final case class CreateEditRequest(model: String, input: Optional[String] = Optional.Absent, instruction: String, n: Optional[CreateEditRequest.N] = Optional.Absent, temperature: Optional[Temperature] = Optional.Absent, topP: Optional[TopP] = Optional.Absent) extends Product with Serializable

CreateEditRequest model

model

ID of the model to use. You can use the text-davinci-edit-001 or code-davinci-edit-001 model with this endpoint.

input

The input text to use as a starting point for the edit.

instruction

The instruction that tells the model how to edit the prompt.

n

How many edits to generate for the input and instruction.

temperature

What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or top_p but not both.

topP

An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both.

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Instance Constructors

  1. new CreateEditRequest(model: String, input: Optional[String] = Optional.Absent, instruction: String, n: Optional[CreateEditRequest.N] = Optional.Absent, temperature: Optional[Temperature] = Optional.Absent, topP: Optional[TopP] = Optional.Absent)

    model

    ID of the model to use. You can use the text-davinci-edit-001 or code-davinci-edit-001 model with this endpoint.

    input

    The input text to use as a starting point for the edit.

    instruction

    The instruction that tells the model how to edit the prompt.

    n

    How many edits to generate for the input and instruction.

    temperature

    What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or top_p but not both.

    topP

    An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both.

Value Members

  1. final def !=(arg0: Any): Boolean
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  2. final def ##: Int
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  3. final def ==(arg0: Any): Boolean
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  4. final def asInstanceOf[T0]: T0
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  5. def clone(): AnyRef
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  6. final def eq(arg0: AnyRef): Boolean
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  7. def finalize(): Unit
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  8. final def getClass(): Class[_ <: AnyRef]
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    @native()
  9. val input: Optional[String]
  10. val instruction: String
  11. final def isInstanceOf[T0]: Boolean
    Definition Classes
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  12. val model: String
  13. val n: Optional[CreateEditRequest.N]
  14. final def ne(arg0: AnyRef): Boolean
    Definition Classes
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  15. final def notify(): Unit
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    @native()
  16. final def notifyAll(): Unit
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  17. def productElementNames: Iterator[String]
    Definition Classes
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  18. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
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  19. val temperature: Optional[Temperature]
  20. val topP: Optional[TopP]
  21. final def wait(): Unit
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    @throws(classOf[java.lang.InterruptedException])
  22. final def wait(arg0: Long, arg1: Int): Unit
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    @throws(classOf[java.lang.InterruptedException])
  23. final def wait(arg0: Long): Unit
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