by Seq2Study

ESM-2

Protein language model for embeddings, fine-tuning and variant scoring.

Meta AI (FAIR)

What it does

Protein language model. Input: a protein sequence; output: per-residue and per-sequence embeddings, masked-token likelihoods and variant pseudo-likelihood scores - the standard feature extractor for fitness/liability models and design filters.

Commercial use

Commercial use OK

Licence as writtenMIT License

The Hugging Face model card front-matter declares 'license: mit' for the released weights; the source repo LICENSE is also MIT.

The licence read at the source allows use by a company. Attribution or copyleft conditions may still apply — read the note.

Is commercial use free of charge?

Free for commercial use

Nothing to pay: the licence read at the source grants commercial use with no fee, and the code and weights are public downloads. You still pay for your own compute.

Price and rights are separate: this panel is about money, the panel above is about permission.

When to use it

Default embedding model for property predictors and sequence ranking; the 650M checkpoint runs on one GPU. Its likelihoods track evolutionary plausibility, not binding affinity or developability.

Facts

Maker
Meta AI (FAIR)
Cost for commercial use
Free for commercial use
Compute
Single GPU
Open weights
Yes
Licence
MIT License
Last verified

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