microsoft/Graphormer

Health v2 · maintenance only

Adoption not part of the score

2474 stars · 376 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Graphormer is a deep learning library from Microsoft providing a graph transformer backbone for molecular modeling tasks. It ships pre-trained models and supports PyG, DGL, OGB, and OCP dataset interfaces on a fairseq backbone.

Use cases

• train custom models for molecular property prediction
• run drug discovery ML experiments
• predict quantum properties of molecules like PCQM4M
• model catalysts with the Open Catalyst dataset
• fine-tune pretrained graph transformer models on molecule data

When to choose

• you need a proven graph transformer for molecule-level ML tasks
• you want pretrained molecular models and standard dataset integrations (PyG, DGL, OGB, OCP)
• you are doing AI-for-science research in chemistry or materials

When to avoid

• you need general-purpose graph learning beyond molecules
• you want a lightweight production inference library rather than a research training framework
• you need the most advanced pretrained versions, which are exclusive to Azure Quantum Elements

Facets

library · maturity maintenance

deep-learning machine-learning llm-training machine-learning deep-learning chemistry artificial-intelligence python graph-transformer molecular-modeling ai4science drug-discovery materials-science graph-neural-networks pretrained-models linux gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="microsoft/Graphormer")