Metadata-Version: 2.2
Name: kvq
Version: 0.0.1
Summary: More for Keys, Less for Values: Adaptive KV Cache Quantization 🐍🚀🎉🦕
Author-email: Mohsen Hariri <mohsen.hariri@case.edu>
License: GPL-3.0 License
Keywords: Large Language Models,Cache,Quantization,Compression,Optimization
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/x-rst
License-File: LICENSE
Requires-Dist: importlib-metadata; python_version < "3.8"

==============
kvq
==============

More for Keys, Less for Values: Adaptive KV Cache Quantization


Installation
------------

To install the package, use pip:

.. code-block:: bash

    pip install kvq


Usage
-----

To use the package, import it in your Python code:

.. code-block:: python

    import kvq

    medviz.layered_plot(image_path="dataset/1-1.nii", mask_paths=["dataset/small_bowel.nii", "dataset/1-1-label.nii"], mask_colors=["red", "yellow"], title="Layered Plot")

The `layered_plot` function creates a layered plot of an image and one or more masks. The masks are overlaid on top of the image using the specified colors. The resulting plot can be used to visualize the location of structures or regions of interest in the image.


.. code-block:: python

    import medviz

    medviz.gif(
        image_path="dataset/1-1.nii",
        mask_paths=[
            "dataset/small_bowel.nii",
            "dataset/1-1-label.nii",
            "dataset/vertebrae_L3.nii.gz",
            "dataset/vertebrae_L4.nii.gz",
            "dataset/vertebrae_L5.nii.gz",
        ],
        mask_colors=["red", "yellow", "green", "blue", "purple"],
        title="Expert Annotations",
        interval=70,
        start_slice=30,
        end_slice=130,
        save_path="animation.gif",
    )

The `gif` function creates an animated GIF of an image and one or more masks. The masks are overlaid on top of the image using the specified colors. The resulting GIF can be used to visualize the location of structures or regions of interest in the image.

GitHub repository: https://github.com/mohsenhariri/kvq
