🔍 Click image to zoom
Fine-tuning LLMs — full process
Frequently Asked Questions
What is Model Fine-Tuning?
The process of further training a pre-trained model on a smaller, task-specific dataset to adapt it for a particular use case. Model fine-tuning is a transfer learning technique in which a pre-trained model's weights are updated on a downstream dataset to improve performance on a specific task, domain, or format.
How is Model Fine-Tuning used in practice?
Fine-tuning preserves the general knowledge learned during pre-training while adapting the model's behaviour — tone, format, domain vocabulary, or task structure — to the target application.
Why is Model Fine-Tuning important in AI?
Model Fine-Tuning is a foundational concept in Training Technique. The process of further training a pre-trained model on a smaller, task-specific dataset to adapt it for a particular use case.