What is Fine-Tuning?

Explained

Fine-tuning continues training a pre-trained model (e.g., GPT, Llama) on domain-specific data. It adapts the model to new tasks or vocabularies. Alternative to prompt engineering when more control is needed.

Decision guides that use this term

• RAG vs fine-tuning: which one does your enterprise use case need?
• Open-source vs proprietary LLMs: how should an enterprise choose?
• EU AI Act provider vs deployer: which role are you, and what does each one owe?

Further reading

• Generative AI Data Integration: Prompt Engineering vs. Fine-Tuning for Business

Related terms

• GPT Architecture behind language models like ChatGPT.
• Prompt Input text that guides a model's response.
• Prompt Engineering Systematic design of prompts to improve quality and consistency.
• Training Process of teaching the model with data (pre-training, fine-tuning).
• Agent Agenda The agent’s live plan: ordered steps, open subtasks, and checkpoints toward a goal.
• Agent Planner Component or prompt pattern that proposes multi-step plans before tools run.