mflux-model-porting

What problem does it solve?

Port ML models into mflux/MLX with correctness-first validation, then refactor toward mflux style for maintainable, robust integrations.

Core Features & Use Cases

• Deterministic porting workflow: establish a skeleton port, wire weight mappings, and implement a minimal runner to verify outputs against a reference.
• Incremental validation: run deterministic tests and milestones to guide refactors into shared components.
• Adaptable to model families: suitable for porting diffusion and other ML models into mflux while preserving behavior.

Quick Start

Create a port plan that mirrors a reference model structure in an mflux port directory, implement a minimal port skeleton, and run deterministic tests to validate parity.