Installation

Prerequisites

• Python 3.11

• A CUDA-capable GPU is recommended for training

Step-by-step

# 1. Create and activate a new environment
conda create -n molcraft python=3.11 -y
conda activate molcraft

# 2. Install conda-only tools (xtb, openbabel)
conda install -c conda-forge xtb==6.7.1 openbabel -y

# 3. Install MolCraftDiffusion with PyTorch + PyG + sparse extensions
pip install molcraftdiffusion[gpu] \
    --find-links https://data.pyg.org/whl/torch-2.6.0+cu124.html

# or CPU-only:
pip install molcraftdiffusion[cpu] \
    --extra-index-url https://download.pytorch.org/whl/cpu \
    --find-links https://data.pyg.org/whl/torch-2.6.0+cpu.html

Development / editable install

git clone https://github.com/pregHosh/MolCraftDiffusion
cd MolCraftDiffusion
conda install -c conda-forge xtb==6.7.1 openbabel -y
pip install -e .[gpu] \
    --find-links https://data.pyg.org/whl/torch-2.6.0+cu124.html

Optional dependencies

# Symmetry analysis (requires numpy==1.24.*)
pip install cosymlib

Verifying the installation

MolCraftDiff --help

You should see a list of all available commands: train, generate, predict, eval_predict, analyze, data.

Pre-trained models

Pre-trained checkpoints are available on Hugging Face. We recommend starting from these for any downstream application.