Glossary | AI & Development
Fine-tuning
Adjusting a pre-trained AI model's weights on a smaller, specialised dataset so it performs better on a specific task.
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Fine-tuning takes a pre-trained foundation model and continues training it on a smaller dataset specific to your domain or task. The result is a model that retains general knowledge but is better at, for example, classifying support tickets, drafting in your house style, or generating outputs in a specific format. Modern lightweight fine-tuning techniques such as LoRA and QLoRA make this affordable for small businesses, where full fine-tuning was previously cost prohibitive.
Sources and further reading
Check the source, not just the summary
- OpenAI model optimisation guidedevelopers.openai.com
- LoRA paperarxiv.org
- QLoRA paperarxiv.org
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