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setup.py
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# Copyright 2025 the LlamaFactory team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import re
from setuptools import find_packages, setup
def get_version() -> str:
with open(os.path.join("src", "llamafactory", "extras", "env.py"), encoding="utf-8") as f:
file_content = f.read()
pattern = r"{}\W*=\W*\"([^\"]+)\"".format("VERSION")
(version,) = re.findall(pattern, file_content)
return version
def get_requires() -> list[str]:
with open("requirements.txt", encoding="utf-8") as f:
file_content = f.read()
lines = [line.strip() for line in file_content.strip().split("\n") if not line.startswith("#")]
return lines
def get_console_scripts() -> list[str]:
console_scripts = ["llamafactory-cli = llamafactory.cli:main"]
if os.getenv("ENABLE_SHORT_CONSOLE", "1").lower() in ["true", "y", "1"]:
console_scripts.append("lmf = llamafactory.cli:main")
return console_scripts
extra_require = {
"torch": ["torch>=2.0.0", "torchvision>=0.15.0"],
"torch-npu": ["torch-npu==2.5.1", "torchvision==0.20.1", "decorator"],
"metrics": ["nltk", "jieba", "rouge-chinese"],
"deepspeed": ["deepspeed>=0.17.2,<=0.18.0"],
"liger-kernel": ["liger-kernel>=0.5.5"],
"bitsandbytes": ["bitsandbytes>=0.39.0"],
"hqq": ["hqq"],
"eetq": ["eetq"],
"gptq": ["optimum>=1.24.0", "gptqmodel>=2.0.0"],
"aqlm": ["aqlm[gpu]>=1.1.0"],
"vllm": ["vllm>=0.4.3,<=0.10.0"],
"sglang": ["sglang[srt]>=0.4.5", "transformers==4.51.1"],
"galore": ["galore-torch"],
"apollo": ["apollo-torch"],
"badam": ["badam>=1.2.1"],
"adam-mini": ["adam-mini"],
"mcore": [
"transformer-engine[pytorch]",
"flashinfer-python",
"megatron-bridge",
"megatron-core",
"mcore_adapter @ git+https://github.com/penfever/roll.git#subdirectory=mcore_adapter",
],
"minicpm_v": [
"soundfile",
"torchvision",
"torchaudio",
"vector_quantize_pytorch",
"vocos",
"msgpack",
"referencing",
"jsonschema_specifications",
],
"openmind": ["openmind"],
"swanlab": ["swanlab"],
"dev": ["pre-commit", "ruff", "pytest", "build", "openai"],
"cce": ["cut-cross-entropy @ git+https://github.com/apple/ml-cross-entropy.git"],
"fp8": ["torchao>=0.8.0", "accelerate>=1.10.0"],
"fp8-te": ["transformer_engine[pytorch]>=2.0.0", "accelerate>=1.10.0"],
"hf-kernels": ["kernels>=0.9.0"],
"qwen3-5": [
"transformers>=5.3.0",
"flash-linear-attention",
"causal-conv1d",
],
"fsdp": [
"torch>=2.4.0,<3.0.0",
"accelerate>=1.0.0",
],
}
def main():
setup(
name="llamafactory",
version=get_version(),
author="hiyouga",
author_email="hiyouga@buaa.edu.cn",
description="Unified Efficient Fine-Tuning of 100+ LLMs",
long_description=open("README.md", encoding="utf-8").read(),
long_description_content_type="text/markdown",
keywords=["AI", "LLM", "GPT", "ChatGPT", "Llama", "Transformer", "DeepSeek", "Pytorch"],
license="Apache 2.0 License",
url="https://github.com/hiyouga/LLaMA-Factory",
package_dir={"": "src"},
packages=find_packages("src"),
python_requires=">=3.9.0",
install_requires=get_requires(),
extras_require=extra_require,
entry_points={"console_scripts": get_console_scripts()},
classifiers=[
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: Apache Software License",
"Operating System :: OS Independent",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
],
)
if __name__ == "__main__":
main()