Interactive Tutorials (Python)¶
This collection of Python tutorials are written for running on Jupyter notebooks. The tutorials provide an introduction to the OpenVINO™ toolkit and explain how to use the Python API and tools for optimized deep learning inference. You can run the code one section at a time to see how to integrate your application with OpenVINO libraries.
Notebooks with 
and buttons can be run without installing anything.
Once you have found the tutorial of your interest, just click the button next to
its name and the Jupyter notebook will start it in a new tab of a browser.
Note
Binder and Google Colab are free online services with limited resources. For the best performance and more control, you should run the notebooks locally. Follow the Installation Guide in order to get information on how to run and manage the notebooks on your machine.
More examples along with additional details regarding OpenVINO Notebooks are available in OpenVINO™ Notebooks Github Repository.
The Jupyter notebooks are categorized into following classes:
Below you will find a selection of recommended tutorials that demonstrate inference on a particular model. These tutorials are guaranteed to provide a great experience with inference in OpenVINO:
Image generation with Latent Consistency Model and OpenVINO.
263-latent-consistency-models-image-generation
Subject-driven image generation and editing using BLIP Diffusion and OpenVINO.
258-blip-diffusion-subject-generation
Note
If there are any issues while running the notebooks, refer to the Troubleshooting and FAQ sections in the Installation Guide or start a GitHub discussion.