Struct Classification

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pub struct Classification<'a> {
Show 14 fields pub model: Option<Model>, pub query: Cow<'a, str>, pub examples: Vec<[Cow<'a, str>; 2]>, pub file: Option<Cow<'a, str>>, pub labels: Vec<Cow<'a, str>>, pub search_model: Option<Model>, pub temperature: Option<f32>, pub logprobs: Option<u32>, pub max_examples: Option<u32>, pub logit_bias: HashMap<Cow<'a, str>, i32>, pub return_prompt: Option<bool>, pub return_metadata: Option<bool>, pub expand: Vec<Cow<'a, str>>, pub user: Option<Cow<'a, str>>,
}
Expand description

Given a query and a set of labeled examples, the model will predict the most likely label for the query. Useful as a drop-in replacement for any ML classification or text-to-label task.

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§model: Option<Model>

ID of the engine to use for completion. You can select one of ada, babbage, curie, or davinci.

§query: Cow<'a, str>

Query to be classified.

§examples: Vec<[Cow<'a, str>; 2]>

A list of examples with labels, in the following format: [["The movie is so interesting.", "Positive"], ["It is quite boring.", "Negative"], ...] All the label strings will be normalized to be capitalized. You should specify either examples or file, but not both.

§file: Option<Cow<'a, str>>

The ID of the uploaded file that contains training examples. See upload file for how to upload a file of the desired format and purpose. You should specify either examples or file, but not both.

§labels: Vec<Cow<'a, str>>

The set of categories being classified. If not specified, candidate labels will be automatically collected from the examples you provide. All the label strings will be normalized to be capitalized.

§search_model: Option<Model>

ID of the engine to use for Search. You can select one of ada, babbage, curie, or davinci

§temperature: Option<f32>

What sampling temperature to use. Higher values mean the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer.

§logprobs: Option<u32>

Include the log probabilities on the logprobs most likely tokens, as well the chosen tokens. For example, if logprobs is 5, the API will return a list of the 5 most likely tokens. The API will always return the logprob of the sampled token, so there may be up to logprobs+1 elements in the response. The maximum value for logprobs is 5. If you need more than this, please contact support@openai.com and describe your use case.

§max_examples: Option<u32>

The maximum number of examples to be ranked by Search when using file. Setting it to a higher value leads to improved accuracy but with increased latency and cost.

§logit_bias: HashMap<Cow<'a, str>, i32>

Modify the likelihood of specified tokens appearing in the completion. Accepts a json object that maps tokens (specified by their token ID in the GPT tokenizer) to an associated bias value from -100 to 100. You can use this tokenizer tool (which works for both GPT-2 and GPT-3) to convert text to token IDs. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.

§return_prompt: Option<bool>

If set to true, the returned JSON will include a “prompt” field containing the final prompt that was used to request a completion. This is mainly useful for debugging purposes.

§return_metadata: Option<bool>

A special boolean flag for showing metadata. If set to true, each document entry in the returned JSON will contain a “metadata” field. This flag only takes effect when file is set.

§expand: Vec<Cow<'a, str>>

If set to true, the returned JSON will include a “prompt” field containing the final prompt that was used to request a completion. This is mainly useful for debugging purposes.

§user: Option<Cow<'a, str>>

A unique identifier representing your end-user, which will help OpenAI to monitor and detect abuse.

Trait Implementations§

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impl<'a> Clone for Classification<'a>

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fn clone(&self) -> Classification<'a>

Returns a duplicate of the value. Read more
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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl<'a> Debug for Classification<'a>

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fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more
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impl Default for Classification<'_>

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fn default() -> Self

Returns the “default value” for a type. Read more
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impl<'a> Serialize for Classification<'a>

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fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>
where __S: Serializer,

Serialize this value into the given Serde serializer. Read more

Auto Trait Implementations§

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impl<'a> Freeze for Classification<'a>

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impl<'a> RefUnwindSafe for Classification<'a>

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impl<'a> Send for Classification<'a>

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impl<'a> Sync for Classification<'a>

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impl<'a> Unpin for Classification<'a>

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impl<'a> UnwindSafe for Classification<'a>

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impl<T> Any for T
where T: 'static + ?Sized,

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fn type_id(&self) -> TypeId

Gets the TypeId of self. Read more
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impl<T> Borrow<T> for T
where T: ?Sized,

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fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more
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impl<T> BorrowMut<T> for T
where T: ?Sized,

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fn borrow_mut(&mut self) -> &mut T

Mutably borrows from an owned value. Read more
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impl<T> CloneToUninit for T
where T: Clone,

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unsafe fn clone_to_uninit(&self, dest: *mut u8)

🔬This is a nightly-only experimental API. (clone_to_uninit)
Performs copy-assignment from self to dest. Read more
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impl<T> From<T> for T

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fn from(t: T) -> T

Returns the argument unchanged.

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impl<T> Instrument for T

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fn instrument(self, span: Span) -> Instrumented<Self>

Instruments this type with the provided Span, returning an Instrumented wrapper. Read more
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fn in_current_span(self) -> Instrumented<Self>

Instruments this type with the current Span, returning an Instrumented wrapper. Read more
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impl<T, U> Into<U> for T
where U: From<T>,

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fn into(self) -> U

Calls U::from(self).

That is, this conversion is whatever the implementation of From<T> for U chooses to do.

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where T: Clone,

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type Owned = T

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fn to_owned(&self) -> T

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fn clone_into(&self, target: &mut T)

Uses borrowed data to replace owned data, usually by cloning. Read more
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impl<T, U> TryFrom<U> for T
where U: Into<T>,

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type Error = Infallible

The type returned in the event of a conversion error.
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fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>

Performs the conversion.
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where U: TryFrom<T>,

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type Error = <U as TryFrom<T>>::Error

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where S: Into<Dispatch>,

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Attaches the current default Subscriber to this type, returning a WithDispatch wrapper. Read more