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Attribute
Biological Foundation Models

ESM-1v

Meta AI (FAIR)
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CategoryBiological Foundation Models
CompanyMeta AI (FAIR)
PriceFree Open Source
StatusStatus not confirmed
AvailabilityAvailable on GitHub and PyPI
Last checked20/09/2026
FeaturesState-of-the-art zero-shot variant effect prediction across 41 deep mutational scanning datasets, Ensemble of five distinct models trained on UniRef90 with different random seeds, Captures epistatic and structural constraints directly from evolutionary sequences, Standard benchmark baseline in computational biology for mutation scoring
Entry typeAI Model
Access modeOpen Source
AI roleVariant Effect Prediction
Input dataNot recorded
Output dataNot recorded
Licence conditionsMIT License
Commercial eligibilityPermissive open source release
Compute requirements1x GPU (>= 16GB VRAM) for batch scoring
ValidationNot recorded
TypeMasked protein language model ensemble
Intended useNot recorded
CompatibilityNot recorded
ManufacturerMeta AI
Biological applicationPredicting viral escape, disease-associated mutations, and enzyme thermostability
Research workflowWild-type sequence + candidate mutations -> compute log-likelihood ratio scores
Evidence levelPeer-reviewed research (NeurIPS 2021)
Integration evidencehttps://github.com/facebookresearch/esm
Laboratory handoffGuides directed evolution and deep mutational scanning library design