Tutorials
=========
We have included a few tutorials to demonstrate the usage of |quanda|. To install the library with tutorial dependencies, run:

.. code:: bash

   pip install -e '.[tutorials]'

The tutorials currently included in |quanda| are:

- `Explainers <https://github.com/dilyabareeva/quanda/blob/main/tutorials/demo_explainers.ipynb>`_: shows how different explainers can be used with |quanda|. This tutorial goes through all the explainers that are included in |quanda| and walks through the steps of initializing the ``Explainer`` object, generating explanations and plotting them.
- `Metrics <https://github.com/dilyabareeva/quanda/blob/main/tutorials/demo_metrics.ipynb>`_: shows how to use the metrics in |quanda| to evaluate the performance of a method. This tutorial goes through all the metrics that are included in |quanda| and walks through the steps of initializing the metric and evaluating the performance of a TDA method.
- :doc:`Benchmarks <tutorial_pages/benchmarks>`: shows how to use the benchmarking tools in |quanda| to evaluate a data attribution method. This tutorial includes 3 different examples of benchmarks.
- :doc:`Linear Datamodeling Score (LDS) <tutorial_pages/lds>`: caveats and best practices for the LDS benchmark, including how to precompute and reuse counterfactual subset logits across explainers.

.. toctree::
   :hidden:

   tutorial_pages/benchmarks
   tutorial_pages/lds