Q-TensorFormer / setup.py
Premchandyadav369
Transform Q-TensorFormer into an Information-Value Adaptive Resource Allocation Architecture
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from setuptools import setup, find_packages
with open("README.md", "r", encoding="utf-8") as fh:
long_description = fh.read()
setup(
name="q-tensorformer",
version="4.0.0",
author="Premchan369",
description="Q-TensorFormer: Information-Value Driven Adaptive Resource Allocation in Hybrid Transformers",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://huggingface.co/Premchan369/Q-TensorFormer",
packages=find_packages(include=["src", "src.*"]),
classifiers=[
"Development Status :: 4 - Beta",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python :: 3",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
],
python_requires=">=3.8",
install_requires=[
"torch>=2.0.0",
"transformers>=4.30.0",
"numpy>=1.24.0",
"pyyaml>=6.0",
],
extras_require={
"dev": [
"pytest>=7.0",
"pytest-cov",
"black",
"isort",
"flake8",
],
"full": [
"accelerate>=0.27.0",
"peft>=0.8.0",
"bitsandbytes>=0.41.0",
"wandb>=0.15.0",
],
},
)