Enum FineTuningModel 

#[non_exhaustive]
pub enum FineTuningModel {
    Gpt41_2025_04_14,
    Gpt41Mini_2025_04_14,
    Gpt41Nano_2025_04_14,
    Gpt4oMini_2024_07_18,
    Gpt4o_2024_08_06,
    Gpt4_0613,
    Gpt35Turbo_0125,
    Gpt35Turbo_1106,
    Gpt35Turbo_0613,
    Babbage002,
    Davinci002,
}

Base models that can be used for fine-tuning.

This enum covers all models that can be fine-tuned via the Fine-tuning API (/v1/fine_tuning/jobs). Note that fine-tuning requires specific dated model versions.

Available Models

GPT-4.1 Series (Latest)

• [Gpt41_2025_04_14]: GPT-4.1 for fine-tuning
• [Gpt41Mini_2025_04_14]: GPT-4.1 Mini for fine-tuning
• [Gpt41Nano_2025_04_14]: GPT-4.1 Nano for fine-tuning

GPT-4o Series

• [Gpt4oMini_2024_07_18]: GPT-4o Mini for fine-tuning
• [Gpt4o_2024_08_06]: GPT-4o for fine-tuning

GPT-4 Series

• [Gpt4_0613]: GPT-4 for fine-tuning

GPT-3.5 Series

• [Gpt35Turbo_0125]: GPT-3.5 Turbo for fine-tuning

Example

use openai_tools::common::models::FineTuningModel;

let model = FineTuningModel::Gpt4oMini_2024_07_18;
assert_eq!(model.as_str(), "gpt-4o-mini-2024-07-18");

Reference

See OpenAI Fine-tuning Guide

Variants (Non-exhaustive)

Non-exhaustive enums could have additional variants added in future. Therefore, when matching against variants of non-exhaustive enums, an extra wildcard arm must be added to account for any future variants.

Gpt41_2025_04_14

gpt-4.1-2025-04-14 - GPT-4.1 for fine-tuning

Gpt41Mini_2025_04_14

gpt-4.1-mini-2025-04-14 - GPT-4.1 Mini for fine-tuning

Gpt41Nano_2025_04_14

gpt-4.1-nano-2025-04-14 - GPT-4.1 Nano for fine-tuning

Gpt4oMini_2024_07_18

gpt-4o-mini-2024-07-18 - GPT-4o Mini for fine-tuning

Gpt4o_2024_08_06

gpt-4o-2024-08-06 - GPT-4o for fine-tuning

Gpt4_0613

gpt-4-0613 - GPT-4 for fine-tuning

Gpt35Turbo_0125

gpt-3.5-turbo-0125 - GPT-3.5 Turbo for fine-tuning

Gpt35Turbo_1106

gpt-3.5-turbo-1106 - GPT-3.5 Turbo (older version)

Gpt35Turbo_0613

gpt-3.5-turbo-0613 - GPT-3.5 Turbo (legacy)

Babbage002

babbage-002 - Legacy base model for fine-tuning

Davinci002

davinci-002 - Legacy base model for fine-tuning

Implementations

impl FineTuningModel

pub fn as_str(&self) -> &str

Returns the model identifier string for API requests.

Trait Implementations

impl Clone for FineTuningModel

fn clone(&self) -> FineTuningModel

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Copy for FineTuningModel

impl Debug for FineTuningModel

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

Formats the value using the given formatter.

impl Default for FineTuningModel

fn default() -> FineTuningModel

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for FineTuningModel

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Display for FineTuningModel

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

Formats the value using the given formatter.

impl Eq for FineTuningModel

impl Hash for FineTuningModel

fn hash<__H: Hasher>(&self, state: &mut __H)

Feeds this value into the given Hasher.

fn hash_slice<H>(data: &[Self], state: &mut H)

where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher.

impl PartialEq for FineTuningModel

fn eq(&self, other: &FineTuningModel) -> bool

Equality operator ==.

fn ne(&self, other: &Rhs) -> bool

Inequality operator !=.

impl Serialize for FineTuningModel

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for FineTuningModel