qc_srv_3to8qubit / README.md
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---
license: apache-2.0
tags:
- physics
- diffusion-model
- quantum-information
- quantum-circuits
- genQC
---
# Schmidt-rank-vector generation 3 to 8 qubits
Paper: ["Quantum circuit synthesis with diffusion models"](https://arxiv.org/abs/2311.02041).
![](https://github.com/FlorianFuerrutter/genQC/blob/main/src/assets/inference.png?raw=true)
## Key Features and limitations
- Schmidt-rank-vector (SRV) generation from **3 to 8 qubits**
- Quantum circuits up to **52 gates**
- Training details in the [\[paper-arxiv\]](https://arxiv.org/abs/2311.02041)
- Prompt formatting: `prompt="Generate SRV: [2, 1, 2, 1, 2]"`
- Gate set: `['h', 'cx']`
## Usage
The pre-trained model pipeline can be loaded with [`genQC`](https://github.com/FlorianFuerrutter/genQC). First install or upgrade [`genQC`](https://github.com/FlorianFuerrutter/genQC) using
``` sh
pip install -U genQC
```
Then the model can be loaded by calling
``` python
from genQC.pipeline.diffusion_pipeline import DiffusionPipeline
pipeline = DiffusionPipeline.from_pretrained("Floki00/qc_srv_3to8qubit", "cpu")
```
A guide on how to use this model can be found in the example notebook `0_hello_circuit`
[\[doc\]](https://florianfuerrutter.github.io/genQC/examples/hello_circuit.html)
[\[notebook\]](https://github.com/FlorianFuerrutter/genQC/blob/main/src/examples/0_hello_circuit.ipynb) on the GitHub repository of [`genQC`](https://github.com/FlorianFuerrutter/genQC).
## License
The model weights in this repository are licensed under the [Apache
License
2.0](https://github.com/FlorianFuerrutter/genQC/blob/main/LICENSE.txt).