Add Training Data Transparency section to README

[Irfan-del-droid]

This PR adds a "Training Data Transparency" section to the README.

The repository focuses on inference using pre-trained models, but this was not explicitly documented. This addition clarifies that no training is performed and directs users to original model sources for dataset details.

This improves transparency and helps users better understand the repository scope.

[Irfan-del-droid]

Hi, I’ve addressed the observation by adding a Training Data Transparency section in the README.

This clarifies that the notebooks use pre-trained models and do not involve training.

Let me know if you’d like any refinements or changes. Thanks for your time!

[brmarkus]

Yes,no training, no re-training, no fine-tuning.
However, various model-conversions and -optimizations are shown, like FP32-FP16 conversion or model quantization, or model-weights compressions.

[Irfan-del-droid]

Thanks for pointing this out! I realize my earlier statement was incomplete since I didn’t fully understand the optimization aspects in OpenVino notebook

[Irfan-del-droid]

Thanks for the clarification! I’ve updated the section to better reflect both inference and model optimization workflows in OpenVINO notebooks. Please let me know if any further refinements are needed.