What does this PR do?

Adds a new documentation page for NeMo Automodel, NVIDIA's PyTorch DTensor-native training library for fine-tuning and pretraining
diffusion models at scale. NeMo Automodel integrates directly with Diffusers — it loads pretrained models from the Hugging Face Hub using
Diffusers model classes and generates outputs via Diffusers pipelines with no checkpoint conversion needed.

The new guide covers:

• Supported models (Wan 2.1, FLUX.1-dev, HunyuanVideo 1.5)
• Installation
• Data preparation and preprocessing
• Training configuration (annotated YAML reference)
• Single-node and multi-node training launch
• Generation / inference with fine-tuned checkpoints
• How NeMo Automodel integrates with the Diffusers ecosystem
• Hardware requirements

Before submitting

• This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
• Did you read the contributor guideline?
• Did you read our philosophy doc (important for complex PRs)?
• Was this discussed/approved via a GitHub issue or the forum? Please add a link to it if that's the case.
• Did you make sure to update the documentation with your changes? Here are the
  documentation guidelines, and
  here are tips on formatting docstrings.
• Did you write any new necessary tests?

Who can review?

@stevhliu @sayakpaul