DPACMAN / h100_env2.yaml
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name: dnabind3
channels:
- conda-forge
- defaults
dependencies:
- python=3.10
- pip>=24
# compiled / heavy libs via conda-forge
- numpy>=2.0,<3.0
- scikit-learn>=1.5,<1.7
- pandas>=2.2,<2.3
- matplotlib>=3.8,<3.11
- lxml>=5.2,<6
- lightning=2.5.1
- torchmetrics>=1.3
- dask
- distributed
- dask-ml
# toolchain for JIT/building CUDA extensions (mamba-ssm, Triton kernels)
- cuda-toolkit=12.4
- cmake
- ninja
- pip:
# Force CUDA wheels and keep them from being overwritten by CPU builds
- --index-url=https://download.pytorch.org/whl/cu124
- torch==2.6.0+cu124
# HF stack + hard deps used at runtime
- transformers==4.53.0
- tokenizers>=0.21,<0.22
- safetensors>=0.4.3
- huggingface-hub==0.34.4
- regex
# Your libs
- rootutils==1.0.7
- hydra-core==1.3.2
- hydra-colorlog==1.2.0
- omegaconf==2.3.0
- pymex==0.9.31
- gitpython==3.1.44
- black==25.1.0
- tqdm==4.67.1
- biopython==1.85
- ortools==9.14.6206
- fair-esm==2.0.0
- rich==14.1.0
- wandb==0.21.1
# Mamba + Triton (for CUDA kernels)
- mamba-ssm==2.2.4
- triton>=3.0,<3.5
# your package
- -e .