Document non-Diffusers FP8/NVFP4 ComfyUI export

[jingyu-ml]

What changed

• Add a short guide for a custom checkpoint owned by an arbitrary Python class with attached PyTorch modules.
• Show how to collect selected components into a temporary nn.ModuleDict without creating a Hugging Face or Diffusers model.
• Document the direct low-level packing path: inspect config, pack quantized leaves, hide quantizer state, adapt keys/config, and write one ComfyUI safetensors checkpoint.
• Cover both FP8_DEFAULT_CFG and NVFP4_DEFAULT_CFG, including the NVFP4-only padding, scale swizzling, and second scale.
• Link the guide from the Diffusers example README.

Why

The existing example constructs a Diffusers pipeline and uses the unified Hugging Face exporter. Custom torch-based applications may instead use a regular Python owner with several attached nn.Module components and custom checkpoint naming. They need a pipeline-independent route to ModelOpt's low-level packing APIs plus an explicit loader-specific ComfyUI adapter.

Impact

Documentation only; no runtime behavior changes.

Validation

• pre-commit run --files examples/diffusers/quantization/CUSTOM-TORCH-TO-COMFYUI.md examples/diffusers/README.md
• Both embedded Python snippets parsed successfully with ast.parse.
• Referenced private API definitions and signatures checked against the current source.

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Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 70.31%. Comparing base (d69d5aa) to head (18a3e58).
⚠️ Report is 18 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1991      +/-   ##
==========================================
- Coverage   73.83%   70.31%   -3.52%     
==========================================
  Files         519      525       +6     
  Lines       57960    64384    +6424     
==========================================
+ Hits        42795    45272    +2477     
- Misses      15165    19112    +3947     

Flag	Coverage Δ
unit	54.79% <ø> (-0.45%)	⬇️

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