JEV / code /pyproject.toml
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v0.8.0: continued training to 0.93 epoch with LR annealing — t30k KL 0.0276→0.0210, choice top-1 0.884→0.898, score MAE 0.119→0.103, ECE 0.0014→0.0007
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[build-system]
requires = ["setuptools>=68", "wheel"]
build-backend = "setuptools.build_meta"
[project]
name = "jev-judge"
version = "0.8.0"
description = "Jev-API compatible typed-decision judge distilled onto Qwen3.5/3.8 (qwen3_5 code path)"
requires-python = ">=3.11"
license = { text = "Apache-2.0" }
dependencies = [
"torch>=2.13",
"transformers>=5.16",
"peft>=0.21",
"safetensors>=0.4",
"pyarrow>=15",
"pandas>=2.0",
"numpy>=1.26",
"pyyaml>=6",
"fastapi>=0.110",
"uvicorn>=0.29",
"tqdm>=4.66",
"scikit-learn>=1.4",
]
[project.optional-dependencies]
dev = ["pytest>=8", "httpx>=0.27"]
[tool.setuptools.packages.find]
where = ["src"]
[tool.pytest.ini_options]
testpaths = ["tests"]
addopts = "-ra"
markers = ["gpu: requires a CUDA device and the base model on disk"]