AI Governance Engineer
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Fine-tuning

By Updated

Further training of an existing model on new data to adapt it to a task or domain. It changes the model, so it is a change event with its own evals; for general-purpose AI models, the Commission treats a modifier as a provider only above one third of the original training compute 1.

Developed in
ch. 15, How it is adapted
ch. 18, When a fine-tuner becomes a GPAI provider
Chapters
ch. 15, Deployment · ch. 18, EU AI Act
Source
1 numbered reference, listed below

Where it is used

11 chapters of the Body of Knowledge use the term. Each link opens the first section that does.

Patterns that use this term

2 pattern pages use the term, most mentions first.

  • Downstream modifier (GPAI)

    An actor that fine-tunes or modifies another provider's general-purpose AI model.

  • Reinforcement learning from human feedback (RLHF)

    A way to align a pre-trained model: supervised fine-tuning on human demonstrations, then reinforcement learning against a reward model trained on human…

  • GPAI

    General-purpose AI model: under the AI Act, a model that shows significant generality, can competently perform a wide range of distinct tasks and can be…

  • Provider

    Under the EU AI Act, whoever develops an AI system or general-purpose AI model, or has one developed, and places it on the market or puts it into service…

  • Evals

    Automated tests of a model's or agent's behaviour (capability, safety and adversarial), run as controls, not as one-off research.

Sources

  1. [1] Guidelines on obligations for general-purpose AI providers, FAQ (a modifier becomes a provider only when the modification uses more than one third of the original model's training compute; obligations limited to the modification). European Commission. 2025. https://digital-strategy.ec.europa.eu/en/faqs/guidelines-obligations-general-purpose-ai-providers (verified: primary)

Definitions of legal terms paraphrase the cited text, which governs. Dated statements are as of .

Cite this term

García Aibar, J. (2026). Fine-tuning. In AI Governance Engineering: The Thesis & Body of Knowledge (v0.5.0), Glossary. https://doi.org/10.5281/zenodo.22956197. https://aigovernanceengineer.com/glossary/fine-tuning. CC BY 4.0

BibTeX

@misc{aige2026finetuning,
  author  = {Jorge García Aibar},
  title   = {{Fine-tuning}},
  note    = {Glossary, AI Governance Engineering: The Thesis \& Body of Knowledge, version 0.5.0},
  year    = {2026},
  doi     = {10.5281/zenodo.22956197},
  url     = {https://aigovernanceengineer.com/glossary/fine-tuning}
}