Magma AI unveils Design-Align: a fine-tuning toolkit that preserves token semantics for design models

AI · 5 min read

Design-Align introduces a token anchoring mechanism during fine-tuning that ensures important token identities (like named colors or component IDs) are treated as anchors and not rewritten inadvertently by the model. This is particularly useful for teams adapting general models to proprietary design systems.

The toolkit provides alignment objectives, curated data augmentation strategies to expand token contexts, and evaluation metrics that quantify both semantic fidelity and layout integrity. Magma AI published integration examples for common training backends and gave guidance on dataset preparation for design-specific fine-tuning.

Design-Align is available under a permissive license for commercial use, and Magma AI hopes it will help vendors deliver fine-tuned models that better respect a customer's established tokens and naming schemes—essential for predictable, team-scaled automation in design tooling.