docs: add VLM training demo

[samuelwheeler]

Summary

• add a step-by-step Aurora tutorial for VLM projector training
• size the PixMo-Cap subset for finite 400-step multi-node runs without data repeats
• cover PixMo-Cap preparation, WebDataset conversion, model downloads, DDP launch, and HSDP larger-batch launch
• add training.viz_num_examples so the demo can log 10 image-caption examples per W&B prediction table

Testing

• cloned the PR branch into a fresh directory and ran the install path with the documented Aurora module stack
• downloaded the OLMo 1B and SigLIP2 Base models into a fresh demo-local Hugging Face cache
• prepared a small PixMo-Cap smoke subset and converted it to WebDataset shards
• ran real 2-node DDP and HSDP PBS smoke jobs from the fresh clone
• ran a 400-step DDP PBS job with 10-example W&B prediction tables
• py_compile: src/config.py src/train.py src/training/trainer_native.py src/utils/batch_viz.py