GPT-3.5 Turbo fine-tuning and API updates

GPT-3.5 Turbo fine-tuning and API updates | OpenAI

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August 22, 2023

Product

GPT‑3.5 Turbo fine-tuning and API updates

Developers can now bring their own data to customize GPT‑3.5 Turbo for their use cases.

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Fine-tuning for GPT‑3.5 Turbo is now available, with fine-tuning for GPT‑4 coming this fall. This update gives developers the ability to customize models that perform better for their use cases and run these custom models at scale. Early tests have shown a fine-tuned version of GPT‑3.5 Turbo can match, or even outperform, base GPT‑4‑level capabilities on certain narrow tasks. As with all our APIs, data sent in and out of the fine-tuning API is owned by the customer and is not used by OpenAI⁠, or any other organization, to train other models.

Fine-tuning use cases

Since the release of GPT‑3.5 Turbo, developers and businesses have asked for the ability to customize the model to create unique and differentiated experiences for their users. With this launch, developers can now run supervised fine-tuning to make this model perform better for their use cases.

In our private beta, fine-tuning customers have been able to meaningfully improve model performance across common use cases, such as:

GPT‑3.5 Turbo fine-tuning and API updates

Developers can now bring their own data to customize GPT‑3.5 Turbo for their use cases.

Listen to article

In addition to increased performance, fine-tuning also enables businesses to shorten their prompts while ensuring similar performance. Fine-tuning with GPT‑3.5‑Turbo can also handle 4k tokens—double our previous fine-tuned models. Early testers have reduced prompt size by up to 90% by fine-tuning instructions into the model itself, speeding up each API call and cutting costs.

Fine-tuning is most powerful when combined with other techniques⁠(opens in a new window) such as prompt engineering, information retrieval, and function calling. Check out our fine-tuning guide⁠(opens in a new window) to learn more. Support for fine-tuning with function calling and gpt-3.5-turbo-16k will be coming later this fall.

Fine-tuning steps

Step 1

Prepare your data

{

"messages": [

{ "role": "system", "content": "You are an assistant that occasionally misspells words" },

{ "role": "user", "content": "Tell me a story." },

{ "role": "assistant", "content": "One day a student went to schoool." }

]

}

Step 2

Upload files

curl https://api.openai.com/v1/files \

-H "Authorization: Bearer $OPENAI_API_KEY" \

-F "purpose=fine-tune" \

-F "file=@path_to_your_file"

Step 3

Create a fine-tuning job

curl https://api.openai.com/v1/fine_tuning/jobs \

-H "Content-Type: application/json" \

-d '{

"training_file": "TRAINING_FILE_ID",

"model": "gpt-3.5-turbo-0613"

}'

Once a model finishes the fine-tuning process, it is available to be used in production right away and has the same shared rate limits as the underlying model.

Step 4

Use a fine-tuned model

curl https://api.openai.com/v1/chat/completions \

"model": "ft:gpt-3.5-turbo:org_id",

"role": "system",

"content": "You are an assistant that occasionally misspells words"

},

"role": "user",

"content": "Hello! What is fine-tuning?"

We will also be debuting a fine-tuning UI in the near future, which will give developers easier access to information about ongoing fine-tuning jobs, completed model snapshots, and more.

curl https://api.openai.com/v1/chat/completions \

-H "Content-Type: application/json" \

-H "Authorization: Bearer $OPENAI_API_KEY" \

-d '{

"model": "ft:gpt-3.5-turbo:org_id",

"messages": [

{

"role": "system",

"content": "You are an assistant that occasionally misspells words"

},

{

"role": "user",

"content": "Hello! What is fine-tuning?"

}

]

}'

We will also be debuting a fine-tuning UI in the near future, which will give developers easier access to information about ongoing fine-tuning jobs, completed model snapshots, and more.