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# Tutorials

This is a list of all our tutorials. They are all self-contained ipython notebooks.

|                    | what?                                                                                                                                                                      | Link |
|--------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------|
| **Recipe search** 🍝 | Learn how to do lightning-fast semantic search by distilling a small model. Compare a really tiny model to a larger with one with a better vocabulary. Learn what Fattoush is (delicious). | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/minishlab/model2vec/blob/master/tutorials/recipe_search.ipynb)     |
| **Semantic chunking** 🧩 | Learn how to chunk your text into meaningful segments with [Chonkie](https://github.com/chonkie-inc/chonkie) at lightning-speed. Efficiently query your chunks with [Vicinity](https://github.com/MinishLab/vicinity). | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/minishlab/model2vec/blob/master/tutorials/semantic_chunking.ipynb) |
| **Training a classifier** 🧩 | Learn how to train a classifier using model2vec. Lightning fast, great performance, especially on small datasets | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/minishlab/model2vec/blob/master/tutorials/train_classifier.ipynb) |
