openvino_notebooks is a collection of interactive Jupyter notebooks designed to demonstrate how to build, optimize, and deploy artificial intelligence applications using the OpenVINO toolkit. The repository provides practical tutorials that guide developers through various AI workflows including computer vision, natural language processing, and generative AI tasks. Each notebook demonstrates how to run pre-trained models, optimize inference performance, and deploy models across hardware such as CPUs, GPUs, and specialized accelerators. The tutorials also illustrate how OpenVINO integrates with models from frameworks like PyTorch, TensorFlow, and ONNX to accelerate inference workloads. Many notebooks include end-to-end examples that show how to prepare input data, load optimized models, run inference, and visualize results. The project is particularly useful for developers who want to learn how to optimize machine learning inference pipelines for production environments.
Features
- Interactive Jupyter notebooks demonstrating OpenVINO workflows
- Examples covering computer vision, NLP, and generative AI models
- Integration with models from PyTorch, TensorFlow, and ONNX
- Tutorials for optimizing inference performance on multiple hardware platforms
- Step-by-step demonstrations of model deployment pipelines
- Visualization and evaluation examples for model outputs