OpenAI has announced that developers can now “fine-tune” GPT 3.5 Turbo to suit different use cases. This feature will be available for GPT-4 later this year.
Fine-tuning allows developers to tailor the language model to specific tasks. For example, a business could fine-tune GPT-3.5 Turbo to match its brand voice and tone. Or a developer could teach it always to format API responses as JSON.
According to OpenAI, early testers have used fine-tuning to do things like:
- Make the model’s outputs more consistent and reliably formatted
- Improve how well it follows instructions
- Match a specific brand’s style and messaging
Fine-tuning has also allowed for shorter prompts – up to 90% shorter in some cases. That speeds up API calls and reduces compute costs.
OpenAI states in an announcement:
“Fine-tuning allows businesses to make the model follow instructions better and format responses more reliably. It’s a great way to hone the qualitative feel of the model output.”
Potential Use Cases
Here are some potential use cases where fine-tuning could improve the performance of large language models like GPT-3.5 Turbo:
- Customer service: Tailor the bot’s tone and vocabulary to match a brand
- Advertising: Generate branded taglines, ad copy, social posts
- Translation: Produce more natural, human-sounding translations
- Writing reports: Learn domain-specific formats and terminology
- Code generation: Match the style and conventions of a programming language
- Text summarization: Focus summaries on critical data points like sports scores
When Will GPT-4 Fine-Tuning Be Available?
OpenAI says capabilities for fine-tuning GPT-4 will arrive this fall.
GPT-3.5 Turbo fine-tuning is available now in beta. OpenAI recommends its gpt-3.5-turbo-0613 model for most use cases.
For more on how to utilize fine-tuning, see OpenAI’s help guide.