ONNX runtime integration documentation

Nobody has claimed this yet.

## 🚀 Feature

Add examples and documentation about how to use ONNX runtime within PL:

https://techcommunity.microsoft.com/t5/ai-machine-learning-blog/accelerate-pytorch-transformer-model-training-with-onnx-runtime/ba-p/2540471

### Motivation

I believe there's nothing we need to change within PL, but we should add this to the docs to show the users how to enable it.

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- [**Metrics**](https://github.com/PyTorchLightning/metrics): Machine learning metrics for distributed, scalable PyTorch applications.

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- [**Lightning Transformers**](https://github.com/PyTorchLightning/lightning-transformers): Flexible interface for high-performance research using SOTA Transformers leveraging Pytorch Lightning, Transformers, and Hydra.

cc @borda @rohitgr7

Start with the existing PyTorch Lightning documentation and the linked ONNX Runtime article to understand the intended workflow. Add examples showing how users can enable ONNX Runtime with Lightning, and consider the work done when the documentation clearly explains the setup and usage.

Written by the indexing model from the issue text.