mirror of
https://github.com/hiyouga/LLaMA-Factory.git
synced 2025-11-04 18:02:19 +08:00
117 lines
4.1 KiB
Python
117 lines
4.1 KiB
Python
# Copyright 2025 the LlamaFactory team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import re
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from setuptools import find_packages, setup
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def get_version() -> str:
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with open(os.path.join("src", "llamafactory", "extras", "env.py"), encoding="utf-8") as f:
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file_content = f.read()
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pattern = r"{}\W*=\W*\"([^\"]+)\"".format("VERSION")
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(version,) = re.findall(pattern, file_content)
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return version
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def get_requires() -> list[str]:
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with open("requirements.txt", encoding="utf-8") as f:
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file_content = f.read()
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lines = [line.strip() for line in file_content.strip().split("\n") if not line.startswith("#")]
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return lines
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def get_console_scripts() -> list[str]:
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console_scripts = ["llamafactory-cli = llamafactory.cli:main"]
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if os.getenv("ENABLE_SHORT_CONSOLE", "1").lower() in ["true", "y", "1"]:
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console_scripts.append("lmf = llamafactory.cli:main")
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return console_scripts
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extra_require = {
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"torch": ["torch>=2.0.0", "torchvision>=0.15.0"],
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"torch-npu": ["torch-npu==2.5.1", "torchvision==0.20.1", "decorator"],
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"metrics": ["nltk", "jieba", "rouge-chinese"],
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"deepspeed": ["deepspeed>=0.10.0,<=0.16.9"],
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"liger-kernel": ["liger-kernel>=0.5.5"],
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"bitsandbytes": ["bitsandbytes>=0.39.0"],
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"hqq": ["hqq"],
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"eetq": ["eetq"],
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"gptq": ["optimum>=1.24.0", "gptqmodel>=2.0.0"],
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"aqlm": ["aqlm[gpu]>=1.1.0"],
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"vllm": ["vllm>=0.4.3,<=0.11.0"],
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"sglang": ["sglang[srt]>=0.4.5", "transformers==4.51.1"],
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"galore": ["galore-torch"],
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"apollo": ["apollo-torch"],
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"badam": ["badam>=1.2.1"],
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"adam-mini": ["adam-mini"],
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"minicpm_v": [
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"soundfile",
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"torchvision",
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"torchaudio",
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"vector_quantize_pytorch",
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"vocos",
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"msgpack",
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"referencing",
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"jsonschema_specifications",
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],
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"openmind": ["openmind"],
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"swanlab": ["swanlab"],
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"fp8": ["torchao>=0.8.0", "accelerate>=1.10.0"],
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"fp8-te": ["transformer_engine[pytorch]>=2.0.0", "accelerate>=1.10.0"],
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"fp8-all": ["torchao>=0.8.0", "transformer_engine[pytorch]>=2.0.0", "accelerate>=1.10.0"],
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"dev": ["pre-commit", "ruff", "pytest", "build"],
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}
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def main():
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setup(
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name="llamafactory",
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version=get_version(),
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author="hiyouga",
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author_email="hiyouga@buaa.edu.cn",
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description="Unified Efficient Fine-Tuning of 100+ LLMs",
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long_description=open("README.md", encoding="utf-8").read(),
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long_description_content_type="text/markdown",
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keywords=["AI", "LLM", "GPT", "ChatGPT", "Llama", "Transformer", "DeepSeek", "Pytorch"],
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license="Apache 2.0 License",
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url="https://github.com/hiyouga/LLaMA-Factory",
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package_dir={"": "src"},
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packages=find_packages("src"),
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python_requires=">=3.9.0",
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install_requires=get_requires(),
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extras_require=extra_require,
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entry_points={"console_scripts": get_console_scripts()},
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classifiers=[
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"Development Status :: 4 - Beta",
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"Intended Audience :: Developers",
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"Intended Audience :: Education",
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"Intended Audience :: Science/Research",
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"License :: OSI Approved :: Apache Software License",
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"Operating System :: OS Independent",
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3.9",
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"Programming Language :: Python :: 3.10",
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"Programming Language :: Python :: 3.11",
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"Programming Language :: Python :: 3.12",
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"Topic :: Scientific/Engineering :: Artificial Intelligence",
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],
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)
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if __name__ == "__main__":
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main()
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