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qc_unitary_3qubit
Floki00/qc_unitary_3qubit
qc_unitary_3qubit is a machine learning model from Floki00. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Paper: "Quantum circuit synthesis with diffusion models".
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Aug 26, 2024
- Updated
- Jun 3, 2025
- SHA
- e12810ea
Model card
From the Hugging Face model README
Unitary compilation 3 qubits
Paper: "Quantum circuit synthesis with diffusion models".
Key Features and limitations
- Unitary compilation on 3 qubits
- Quantum circuits up to 12 gates
- Training details in the [paper-arxiv]
- Prompt formatting:
prompt="Compile using: ['h', 'cx', 'z', 'x', 'ccx', 'swap']" - Gate set:
['h', 'cx', 'z', 'x', 'ccx', 'swap']
Usage
The pre-trained model pipeline can be loaded with genQC. First install or upgrade genQC using
pip install -U genQC
Then the model can be loaded by calling
from genQC.pipeline.diffusion_pipeline import DiffusionPipeline
pipeline = DiffusionPipeline.from_pretrained("Floki00/qc_unitary_3qubit", "cpu")
A guide on how to use this model can be found in the example notebook 2_unitary_compilation[doc] on the GitHub repository of genQC.
License
The model weights in this repository are licensed under the Apache License 2.0.
- License
- apache-2.0
- Created
- Aug 26, 2024
- Updated
- Jun 3, 2025