Detailed explanation
Examples
Frequently asked questions
When should I fine-tune rather than use RAG?
Fine-tune for style, format, or behavior. Use RAG to inject up-to-date or proprietary knowledge. The two are complementary.
How many examples are needed to fine-tune?
For LoRA on an LLM, 100 to 1,000 high-quality examples are often enough. Quality beats quantity.
Related terms
Machine Learning
A branch of AI where models learn patterns from data instead of following explicit rules.
Distillation
A process that trains a small "student" model to mimic a large "teacher" model, keeping quality at lower cost.
LLM (Large Language Model)
An LLM is a large language model trained on massive text corpora, capable of understanding and generating natural language across many tasks: writing, summarization, translation, code, reasoning.
Quantization
A technique that reduces the numerical precision of a model's weights to make it lighter and faster.
Dataset
A structured collection of data used to train, validate or evaluate an AI model.
Last updated: 7/15/2026