Quantinuum/Quixer
Code repository for the preprint "Quixer: A Quantum Transformer Model"
Quixer helps quantum machine learning researchers and practitioners explore a novel quantum transformer model architecture. It takes in textual data (or other sequential data types) and outputs predictions based on the learned patterns, similar to classical deep learning models. This project is for researchers developing or evaluating advanced machine learning models, particularly those interested in quantum computing's application to sequence processing.
No commits in the last 6 months.
Use this if you are a quantum machine learning researcher or a deep learning practitioner interested in exploring the practical implementation and simulation of a quantum-inspired transformer model alongside classical baselines.
Not ideal if you are looking for a pre-trained, production-ready model for immediate application, or if you do not have a strong background in deep learning and quantum computing concepts.
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Language
Python
License
Apache-2.0
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Last pushed
Jun 20, 2025
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