mini-posttrain/pyproject.toml at main · AMark-CS/mini-posttrain · GitHub

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[build-system]
requires = ["setuptools>=68", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "mini-posttrain"
version = "0.1.0"
description = "A teaching-level post-training library: SFT + DPO in <1000 LoC, designed to be read in a Sunday afternoon."
readme = "README.md"
license = { text = "Apache-2.0" }
authors = [{ name = "Mark" }]
keywords = ["llm", "post-training", "sft", "dpo", "lora", "rlhf"]
classifiers = [
    "Development Status :: 3 - Alpha",
    "Intended Audience :: Education",
    "Intended Audience :: Science/Research",
    "License :: OSI Approved :: Apache Software License",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
]
requires-python = ">=3.10"
dependencies = [
    "torch>=2.1",
    "transformers>=4.40",
    "numpy",
]

[project.optional-dependencies]
peft = ["peft>=0.10"]
trl = ["trl>=0.10", "datasets>=2.20"]
wandb = ["wandb>=0.16"]
dev = [
    "pytest>=8",
    "ruff>=0.4",
    "datasets>=2.20",
    "trl>=0.10",
    "peft>=0.10",
    "wandb>=0.16",
]

[project.scripts]
mini-sft = "mini_posttrain.cli.train_sft:main"
mini-dpo = "mini_posttrain.cli.train_dpo:main"
mini-eval = "mini_posttrain.eval.eval_harness:main"

[tool.setuptools.packages.find]
include = ["mini_posttrain*"]

[tool.pytest.ini_options]
markers = [
    "smoke: opt-in tests that download a tiny model and run end-to-end",
]
testpaths = ["tests"]

[tool.ruff]
line-length = 100
target-version = "py310"