semvec/pypi-packages huggingface dataset:
diffusionq 0.1.0
quantizing your diffusion models efficiently and accurately
Requires Python: >=3.6

# diffusionq

`diffusionq` is a Python package designed for quantizing pre-trained diffusion models. By using `diffusionq`, you can efficiently quantize your models to save memory and accelerate inference, making it easier to deploy these models in resource-constrained environments.

## Installation

To install `diffusionq`, simply run the following command:

```bash
pip install diffusionq
```

## Usage
Using diffusionq is straightforward. Once you have a pre-trained diffusion model, you can quantize it by following these steps:

```python
from diffusionq import QuantModel

# Assuming 'model' is your pre-trained diffusion model
quant_model = QuantModel(model)

# Now 'quant_model' is the quantized version of your original model
# You can use 'quant_model' for your inference tasks
```

## Features
Easy Integration: Seamlessly quantize pre-trained diffusion models with just one line of code.
Memory Efficiency: Reduce the memory footprint of your models significantly.
Faster Inference: Enjoy faster model inference, especially beneficial for deploying models on edge devices.

## Contributing
Contributions to diffusionq are welcome! If you have suggestions for improvements or encounter any issues, please feel free to open an issue or submit a pull request.

## Contact
For any queries or further assistance with diffusionq, please reach out to Your Name.