# Recommended install order (avoids DeepSpeed / torch / setuptools pitfalls):
# 1) Use Python 3.10 (matches repo classifiers; avoid 3.13+).
# 2) Install CUDA-enabled PyTorch first (CUDA major should match nvcc below, e.g. 12.4):
#    pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124
# 3) If the system has no full CUDA toolkit, install nvcc via conda and set CUDA_HOME (DeepSpeed checks this on import):
#    conda install -y cuda-nvcc=12.4 -c nvidia
#    export CUDA_HOME="${CUDA_HOME:-$CONDA_PREFIX}"
# 4) Then: pip install -r requirements.txt && pip install -e .

# Newer setuptools drops pkg_resources; this repo still imports it (see lmflow.utils.versioning).
setuptools>=64,<81

packaging
numpy
datasets==2.14.6
tokenizers>=0.13.3
peft>=0.10.0
torch>=2.0.1
wandb
deepspeed>=0.14.4
sentencepiece
transformers==4.53.1
cpm_kernels==1.0.11
evaluate==0.4.0
bitsandbytes>=0.40.0
pydantic
accelerate>=0.27.2
einops>=0.6.1
pyarrow==18.0.0