AI Glossary
What is Fine-tuning?
The process of further training a pre-trained AI model on a specific dataset to improve its performance on a particular task or domain.
Fine-tuning explained
Fine-tuning is an advanced AI technique where you take a base model (like GPT-3.5 or Llama 3) and train it further on your own data. This can make the model much better at specific tasks — like writing in your brand's tone, answering questions about your product, or following industry-specific conventions. Fine-tuning requires labeled training data and significant compute resources, making it more complex than prompt engineering.
Frequently asked questions
What is fine-tuning in AI?
Fine-tuning is the process of taking a pre-trained AI model and training it further on your own data to improve its performance on specific tasks or domains.
Do I need fine-tuning or just better prompts?
For most use cases, better prompts and AI skills are sufficient and far cheaper than fine-tuning. Fine-tuning is worth considering when you need consistent style/format at high volume or domain-specific accuracy.
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