Add Training Data Transparency section to README

README.md

@@ -228,6 +228,26 @@ Made with [`contrib.rocks`](https://contrib.rocks).
 * [What is the first CPU generation you support with OpenVINO?](https://www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/system-requirements.html)
 * [Are there any success stories about deploying real-world solutions with OpenVINO?](https://www.intel.com/content/www/us/en/internet-of-things/ai-in-production/success-stories.html)
 
+## 🔍 Training Data Transparency
+
+This repository focuses on demonstrating **inference and model optimization workflows** using the OpenVINO™ Toolkit with pre-trained models.
+
+- The notebooks do **not perform model training, re-training, or fine-tuning**.
+- Instead, they leverage pre-trained models and showcase **efficient inference and deployment techniques** across different hardware backends.
+- In addition to inference, the notebooks demonstrate **model optimization workflows**, including:
+  - model conversion (e.g., FP32 → FP16 / INT8)
+  - quantization and compression techniques
+  - performance tuning for CPU, GPU, and other supported devices
+
+Training data details, dataset composition, and associated biases are defined by the **original model providers** and are not modified within this repository.
+
+Users are encouraged to:
+- Review the original model documentation for dataset sources and training details
+- Understand potential biases and limitations of pre-trained models
+- Evaluate models appropriately for their specific use cases and deployment environments
+- Follow responsible AI and data governance practices when integrating these models into applications
+
+This section aims to clarify the scope of the repository and improve transparency regarding how models are used within OpenVINO notebooks.
 ---
 
 \* Other names and brands may be claimed as the property of others.