Struct async_openai::types::CreateEditRequest
source · pub struct CreateEditRequest {
pub model: String,
pub input: Option<String>,
pub instruction: String,
pub n: Option<u8>,
pub temperature: Option<f32>,
pub top_p: Option<f32>,
}
Fields§
§model: String
ID of the model to use. You can use the text-davinci-edit-001
or code-davinci-edit-001
model with this endpoint.
input: Option<String>
The input text to use as a starting point for the edit.
instruction: String
The instruction that tells the model how to edit the prompt.
n: Option<u8>
How many edits to generate for the input and instruction.
temperature: Option<f32>
What sampling temperature to use. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer.
We generally recommend altering this or top_p
but not both.
top_p: Option<f32>
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.
Trait Implementations§
source§impl Clone for CreateEditRequest
impl Clone for CreateEditRequest
source§fn clone(&self) -> CreateEditRequest
fn clone(&self) -> CreateEditRequest
1.0.0 · source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read moresource§impl Debug for CreateEditRequest
impl Debug for CreateEditRequest
source§impl Default for CreateEditRequest
impl Default for CreateEditRequest
source§fn default() -> CreateEditRequest
fn default() -> CreateEditRequest
source§impl PartialEq for CreateEditRequest
impl PartialEq for CreateEditRequest
source§fn eq(&self, other: &CreateEditRequest) -> bool
fn eq(&self, other: &CreateEditRequest) -> bool
self
and other
values to be equal, and is used
by ==
.