Project Overview

torch-molecule is a package under active development to support molecular discovery using deep learning. It provides a simple, sklearn-style interface and model checkpoints for fast deployment and benchmarking.

Main components:

  1. Predictive Models - ✔ GREA, SGIR, IRM, GIN/GCN w/ virtual, DIR - ✔ SMILES-based LSTM/Transformers - ⏳ More models

  2. Generative Models - ✔ Graph DiT, GraphGA, DiGress, MolGPT - ⏳ GDSS and more

  3. Representation Models - ✔ MoAMa, AttrMasking, ContextPred, EdgePred, InfoGraph - ⏳ more models and pretrained checkpoints

Note

This project is in active development. Interfaces and features may change.

Project Structure

torch_molecule
├── base
├── encoder
├── generator
├── nn
├── predictor
└── utils

Acknowledgements

This project was adapted from python-project-template.