# OpenVINO Tokenizers: Incorporate Text Processing Into OpenVINO Pipelines [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/eaidova/openvino_notebooks_binder.git/main?urlpath=git-pull%3Frepo%3Dhttps%253A%252F%252Fgithub.com%252Fopenvinotoolkit%252Fopenvino_notebooks%26urlpath%3Dtree%252Fopenvino_notebooks%252Fnotebooks%2Fopenvino-tokenizers%2Fopenvino-tokenizers.ipynb) [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/openvino-tokenizers/openvino-tokenizers.ipynb)
OpenVINO Tokenizers is an OpenVINO extension and a Python library designed to streamline tokenizer conversion for seamless integration into your projects. It supports Python and C++ environments and is compatible with all major platforms: Linux, Windows, and MacOS. ## Notebook Contents The tutorial consists of the following steps: - Explain the basics of tokenization - Install OpenVINO Tokenizers - Convert tokenizer from HuggingFace Hub using CLI and Python API - Create a Text Generation pipeline with OpenVINO tokenizer and detokenizer - Combine an OpenVINO tokenizer with a classification model ## Installation Instructions This is a self-contained example that relies solely on its own code.
We recommend running the notebook in a virtual environment. You only need a Jupyter server to start. For details, please refer to [Installation Guide](../../README.md).