Suggestion: add a Stable Fast 3D (SF3D) example — native MLX single-image-to-3D-mesh

Title: Suggestion: add a Stable Fast 3D (SF3D) example — native MLX single-image-to-3D-mesh

mlx-examples currently has no example for feedforward 3D mesh reconstruction (closest is stable_diffusion, which is 2D image generation). Stable Fast 3D (Stability AI) is a strong single-image → textured 3D mesh model, and its official PyTorch/CUDA implementation runs quite slowly on Mac via MPS (~7-9 min/generation on an M1 Pro).

I've ported the full inference pipeline natively to MLX — neural forward pass (camera embedder, DINOv2 tokenizer + AdaLN modulation, two-stream transformer backbone, post-processor, triplane decoder) plus UV-unwrap/texture-baking finishing, validated module-by-module against the original PyTorch model to float32 tolerance. End-to-end time on the same M1 Pro dropped to ~12.4s (~34-44x faster).

Repo (Derivative Work under the Stability AI Community License, "Powered by Stability AI"): https://github.com/bahaehmimdi/stable-fast-3d-mlx

Would a stable_fast_3d example (adapted to mlx-examples' structure/conventions) be welcome as a contribution here? Happy to open a PR if so — wanted to check interest/fit first given the license terms on the underlying model.

Start by reviewing the existing stable_diffusion example and the linked stable-fast-3d-mlx repository, then check how its derivative-work license fits mlx-examples contribution conventions. Done means an adapted stable_fast_3d example follows the repository's structure and conventions, with the maintainers confirming that the model and license are appropriate.