File size: 3,775 Bytes
bc55b34 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 |
# Copyright 2024 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 typing import List
from setuptools import find_packages, setup
def get_version() -> str:
with open(os.path.join("src", "llamafactory", "extras", "env.py"), "r", 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", "r", 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.environ.get("ENABLE_SHORT_CONSOLE", "1").lower() in ["true", "1"]:
console_scripts.append("lmf = llamafactory.cli:main")
return console_scripts
extra_require = {
"torch": ["torch>=1.13.1"],
"torch-npu": ["torch==2.1.0", "torch-npu==2.1.0.post3", "decorator"],
"metrics": ["nltk", "jieba", "rouge-chinese"],
"deepspeed": ["deepspeed>=0.10.0,<=0.14.4"],
"liger-kernel": ["liger-kernel"],
"bitsandbytes": ["bitsandbytes>=0.39.0"],
"hqq": ["hqq"],
"eetq": ["eetq"],
"gptq": ["optimum>=1.17.0", "auto-gptq>=0.5.0"],
"awq": ["autoawq"],
"aqlm": ["aqlm[gpu]>=1.1.0"],
"vllm": ["vllm>=0.4.3,<=0.6.3"],
"galore": ["galore-torch"],
"badam": ["badam>=1.2.1"],
"adam-mini": ["adam-mini"],
"qwen": ["transformers_stream_generator"],
"modelscope": ["modelscope"],
"openmind": ["openmind"],
"dev": ["ruff", "pytest"],
}
def main():
setup(
name="llamafactory",
version=get_version(),
author="hiyouga",
author_email="hiyouga" "@" "buaa.edu.cn",
description="Easy-to-use LLM fine-tuning framework",
long_description=open("README.md", "r", encoding="utf-8").read(),
long_description_content_type="text/markdown",
keywords=["LLaMA", "BLOOM", "Falcon", "LLM", "ChatGPT", "transformer", "pytorch", "deep learning"],
license="Apache 2.0 License",
url="https://github.com/hiyouga/LLaMA-Factory",
package_dir={"": "src"},
packages=find_packages("src"),
python_requires=">=3.8.0",
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 :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
],
)
if __name__ == "__main__":
main()
|