BioNeMo Recipes (NVIDIA)
github.com/nvidia-bionemo/bionemo-recipesTransformerEngine-accelerated checkpoints and training recipes for scaling biological foundation models (ESM-2, AMPLIFY, Geneformer, CodonFM) from single-GPU prototyping to multi-node FSDP training with FP8/MXFP8/NVFP4 precision, compatible with PyTorch, HF Accelerate, and PyTorch Lightning, plus sparse-autoencoder interpretability tools for biological foundation models (851+ stars, 2026)
Sourced from
- Awesome AI for Science — github.com/nvidia-bionemo/bionemo-recipes
- GitHub — github.com/nvidia-bionemo/bionemo-recipes
Related resources
NVIDIA's open-source platform for building and adapting biological AI models at scale, bundling ESM-2, Geneformer, MolMIM and DNA embedding models with recipes for single-GPU to multi-node training (2025)
E(3)-equivariant neural network interatomic potentials achieving DFT accuracy with up to 1000× less training data than invariant models, foundational architecture behind MACE and Allegro (Harvard, MIT, Nature Communications 2022)
OpenChem is a deep learning toolkit for Computational Chemistry with PyTorch backend.
Highly scalable equivariant deep learning interatomic potentials enabling million-atom molecular dynamics simulations with ab initio accuracy, building on E(3)-equivariant architectures for large-scale atomistic modeling (mir-group, MIT License, 480+ stars)
Deep learning library for Chemistry based on Tensorflow
Open-source framework for building physics-ML models at scale (renamed from Modulus, 2025)