lambeq

Closed bounties:

• $250 | UnitaryHACK: Serialise ansatz and include in model
  closed by: neiljdo
• $150 | UnitaryHACK: Implement and test gradient free optimizer for circuit models
  closed by: Gopal-Dahale
• $100 | UnitaryHACK: Replace unknown words in diagrams with UNK token
  closed by: WingCode, ACE07-Sev

lambeq is an open-source, modular, extensible high-level Python library for experimental 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 quantum circuit, based on a given compositional model and certain parameterisation and choices of ansätze, and facilitates training for both quantum and classical NLP experiments.