CUDA Quantum streamlines hybrid application development and promotes productivity and scalability in quantum computing. It offers a unified programming model designed for a hybrid setting—that is, CPUs, GPUs, and QPUs working together.
For more information, see the [official documentation][1].
## How to Install Version Without GPU Acceleration
Use (preferably in conda environment)
```bash
pip install cuda-quantum
```
## How to Install Version With GPU Acceleration Using Conda
Run:
```bash
conda create -y-n cuda-quantum python=3.10 pip
conda install-y-n cuda-quantum -c"nvidia/label/cuda-11.8.0" cuda
You can test your installation by running the following script:
```bash
import cudaq
kernel = cudaq.make_kernel()
qubit = kernel.qalloc()
kernel.x(qubit)
kernel.mz(qubit)
result = cudaq.sample(kernel)
```
## Further Questions Considering the Installation?
See the Cuda Quantum PyPI website at [https://pypi.org/project/cuda-quantum/][2].
## Example QNN:
In the *qnn_example.py* you find a script that loads FashionMNIST dataset, chooses two data type (shirts and pants), then we create a Neural Network with quantum layer.This network is then trained on our data and later tested on the test dataset. You are free to try it on your own. Download the [QNN example][a] and rename it to `qnn_example.py`.