What is lambeq? =============== ``lambeq`` is an open-source, modular, extensible high-level Python library for experimental :term:`Quantum Natural Language Processing ` (QNLP), created by `Quantinuum `_'s QNLP team. At a high level, the library allows the conversion of any sentence to a :term:`quantum circuit`, based on a given :term:`compositional model` and certain parameterisation and choices of :term:`ansätze `, and facilitates :ref:`training ` for both quantum and classical NLP experiments. The notes for the latest release can be found :ref:`here `. ``lambeq`` is available for Python 3.10 and higher, on Linux, macOS and Windows. To install, type: .. code-block:: bash pip install lambeq or refer to :ref:`sec-installation` for more information. To start the tutorial, go to `Step 1: Sentence Input `_. To see the example notebooks, go to :ref:`sec-examples`. To use the command-line interface, read :ref:`sec-cli`. To make your own contributions to ``lambeq``, see :ref:`sec-contributing`. Licence ------- Licensed under the `Apache 2.0 License `_. User support ------------ If you need help with ``lambeq`` or you think you have found a bug, please send an email to lambeq-support@quantinuum.com. You can also open an issue at ``lambeq``'s `GitHub repository `_. Someone from the development team will respond to you as soon as possible. Furthermore, if you want to subscribe to ``lambeq``'s mailing list (lambeq-users@quantinuum.com), send an email to lambeq-support@quantinuum.com to let us know. Note that the best way to get in touch with the QNLP community and learn about ``lambeq`` is to join our `QNLP discord server `_, where you can ask questions, get notified about important announcements and news, and chat with other QNLP researchers. How to cite ----------- If you use ``lambeq`` for your research, please cite the accompanying paper :cite:p:`kartsaklis_2021`: .. code-block:: bash @article{kartsaklis2021lambeq, title={lambeq: {A}n {E}fficient {H}igh-{L}evel {P}ython {L}ibrary for {Q}uantum {NLP}}, author={Dimitri Kartsaklis and Ian Fan and Richie Yeung and Anna Pearson and Robin Lorenz and Alexis Toumi and Giovanni de Felice and Konstantinos Meichanetzidis and Stephen Clark and Bob Coecke}, year={2021}, journal={arXiv preprint arXiv:2110.04236}, }