Update README.md

README.md

@@ -1,3 +1,47 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+tags:
+- physics
+- diffusion-model
+- quantum-information
+- quantum-circuits
+- genQC
+---
+
+# Unitary compilation 3 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
+
+- Unitary compilation on **3 qubits**
+- Quantum circuits up to **12 gates**
+- Training details in the [\[paper-arxiv\]](https://arxiv.org/abs/2311.02041)
+- 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`](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_unitary_3qubit", "cpu")
+```
+
+A guide on how to use this model can be found in the example notebook `2_unitary_compilation`[\[doc\]](https://florianfuerrutter.github.io/genQC/examples/unitary_compilation.html) [\[notebook\]](https://github.com/FlorianFuerrutter/genQC/blob/main/src/examples/2_unitary_compilation.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).