A HF/Docker/Modal reproducible training/inference example

Considering that it depends on specific torch (torch==2.2.1) and possibly CUDA, many MacBooks won't be able to run some of the examples. If you want to run tests and notebooks, you'll need lfs and so on - so it becomes an infra nightmare.

1. Is there any plan to create a template for training/inference on Docker / Modal.com, using say `pytorch/pytorch:2.2.1-cuda12.1-cudnn8-devel`?
2. Is there any plan to create a HuggingFace space on at least one of the 10+ demos?
3. I see that pip install with mlx support already requires `huggingface_hub`. Is there a reason why?

The issue names no files, tests, or entry points; begin by reviewing the existing training and inference demos, notebooks, and their dependency setup. Compare the requested Docker/Modal and Hugging Face approaches, then establish a concrete scope and acceptance criteria for a reproducible example and the mlx-support dependency rationale.

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