| # 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 | |