Lesson Content

What fine-tuned models are.

Fine-tuned models are models trained on additional data beyond the base model – producing more specialized or consistent output for the focus area of their training. Fine-tuning can emphasize a specific art style, a specific subject category (anime characters, realistic portraits, specific environments), or a specific aesthetic treatment. Leonardo AI provides both platform-created fine-tunes and access to community-trained fine-tuned models.

Finding models in Leonardo AI.

The model library in Leonardo AI shows available models including community fine-tunes, filterable by category, style, and rating. Model pages typically show example generations and basic training information – review these before using an unfamiliar fine-tuned model to understand what it produces and for what content types it's optimized.

Evaluating community fine-tuned models.

Community models vary significantly in quality and training focus – some are professionally trained for specific production uses; others are experimental or niche. Evaluation approach: review the model's example generations carefully, check the model's rating and usage statistics (popular, well-rated models have been validated by other users), and test on a small prompt before production use.

Using fine-tuned models effectively.

Fine-tuned models often work best with specific prompt language aligned with their training – check any available model documentation for recommended prompt approaches. Some fine-tunes produce strong results with minimal prompting; others require specific trigger words or prompt structures that align with their training.