Fine Tuning

7 items tagged with "fine-tuning"

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Best Practices1

Fine-Tuning vs RAG Decision Framework

A decision framework for choosing between fine-tuning, RAG, or both, based on whether the goal is new knowledge, consistent behavior, freshness, or domain adaptation.

Tutorials1

Tutorial

How to fine-tune a language model on your own data

Adapt a base language model to your domain with supervised fine-tuning, covering data prep, training, and evaluation.

Comparisons2

Comparison

RAG vs Fine-Tuning

Retrieval-augmented generation injects external knowledge at query time; fine-tuning bakes behavior into model weights. They solve different problems and often combine.

Comparison

Fine-Tuning vs Prompt Engineering

Prompt engineering steers a model with instructions and examples in the context; fine-tuning changes the weights. Cost, control, and durability differ sharply.

FAQs2

FAQ

What is the difference between fine-tuning and RAG?

Fine-tuning updates a model's weights by training it further on domain-specific examples, changing how the model behaves and what style or skills it h...

FAQ

What is fine-tuning a model?

Fine-tuning is the process of continuing to train a pre-trained model on a smaller, task-specific dataset so it adapts to a particular domain, style, ...

Glossaries1

Glossary

Fine-Tuning

Fine-tuning is the process of further training a pretrained model on a smaller, task-specific dataset to specialize its behavior, style, or domain knowledge.