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setup the Documentation.
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+69
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.readthedocs.yaml

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@@ -4,6 +4,10 @@ build:
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os: ubuntu-22.04
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tools:
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python: "3.8"
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jobs:
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pre_build:
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- pip install --upgrade pip setuptools wheel
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- pip install torch --index-url https://download.pytorch.org/whl/cpu
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sphinx:
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configuration: docs/conf.py
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path: .
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extra_requirements:
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- dev
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- requirements: docs/requirements.txt
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formats:
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- pdf

docs/requirements.txt

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@@ -3,15 +3,6 @@ sphinx-rtd-theme>=1.0.0
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sphinx-copybutton>=0.5.0
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sphinx-autodoc-typehints>=1.18.3
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myst-parser>=0.18.1
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# Package dependencies
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# Only include minimal package dependencies for docs building
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torch>=2.0.0
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transformers>=4.30.0
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datasets>=2.12.0
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accelerate>=0.20.0
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peft>=0.4.0
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bitsandbytes>=0.40.0
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scipy>=1.10.0
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scikit-learn>=1.0.0
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tqdm>=4.65.0
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numpy>=1.24.0
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wandb>=0.15.0
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transformers>=4.30.0

setup.py

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from setuptools import setup, find_packages
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with open("README.md", "r", encoding="utf-8") as fh:
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long_description = fh.read()
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with open("requirements.txt", "r", encoding="utf-8") as fh:
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requirements = [line.strip() for line in fh if line.strip() and not line.startswith("#")]
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setup(
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name="quantllm",
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version="0.1.0",
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author="Dark Coder",
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author_email="[email protected]",
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description="A lightweight library for quantized LLM fine-tuning and deployment",
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long_description=long_description,
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long_description_content_type="text/markdown",
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url="https://github.com/codewithdark-git/QuantLLM",
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packages=find_packages(),
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classifiers=[
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"Development Status :: 3 - Alpha",
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"Intended Audience :: Science/Research",
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"License :: OSI Approved :: MIT License",
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"Operating System :: OS Independent",
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3.8",
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"Programming Language :: Python :: 3.9",
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"Topic :: Scientific/Engineering :: Artificial Intelligence",
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],
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python_requires=">=3.8",
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install_requires=requirements,
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extras_require={
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"dev": [
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"sphinx>=4.5.0",
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"sphinx-rtd-theme>=1.0.0",
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"sphinx-copybutton>=0.5.0",
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"sphinx-autodoc-typehints>=1.18.3",
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"myst-parser>=0.18.1",
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"pytest>=7.0.0",
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"pytest-cov>=3.0.0",
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"black>=22.0.0",
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"isort>=5.10.0",
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"flake8>=4.0.0",
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"torch>=2.0.0",
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"transformers>=4.30.0",
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"datasets>=2.12.0",
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"accelerate>=0.20.0",
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"peft>=0.4.0",
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"bitsandbytes>=0.40.0",
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"scipy>=1.10.0",
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"scikit-learn>=1.0.0",
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"tqdm>=4.65.0",
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"numpy>=1.24.0",
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"wandb>=0.15.0",
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"sentencepiece>=0.1.99",
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"protobuf>=3.20.0",
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"einops>=0.6.1",
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"evaluate>=0.4.0",
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"tensorboard>=2.13.0"
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],
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},
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include_package_data=True,
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zip_safe=False,
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)

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