facebookresearch/esm

Health v2 · maintenance only

Flags: archived

Adoption not part of the score

4170 stars · 804 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Meta FAIR's Evolutionary Scale Modeling (ESM) library providing Transformer protein language models with pretrained weights, including ESM-2, ESMFold, MSA Transformer, ESM-1v, and ESM-IF1. It supports protein structure prediction, variant effect prediction, embedding generation, and generative protein design.

Use cases

• predict protein 3D structure from amino acid sequence
• generate protein embeddings for downstream ML tasks
• predict effects of mutations on protein function
• design novel de novo proteins with language models
• run inverse folding to design sequences for a target structure
• fine-tune pretrained protein language models in PyTorch

When to choose

• you need state-of-the-art single-sequence protein structure prediction without an MSA
• you want pretrained protein language model weights for research
• you are doing computational biology or protein engineering with PyTorch

When to avoid

• you need a lightweight tool without GPU resources - ESMFold models are large
• you need AlphaFold-style MSA-based predictions with extensive tooling
• you need a maintained production product - the repo is in maintenance mode with newer ESM versions elsewhere

Facets

library · maturity maintenance

machine-learning deep-learning llm-training bioinformatics deep-learning python protein-language-models protein-structure-prediction esmfold pretrained-weights transformers computational-biology natural-language-processing linux gpu

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markdown · JSON · MCP: product_card(name="facebookresearch/esm")