ESM2 Perplexity

License: ESM2 is open source and free for academic and commercial use under an MIT license. Please refer to the license for full terms.

This constraint is open source. Any third-party models, product names, or trademarks referenced are the property of their respective owners, and Proto is not affiliated with them.

Tools Used Tools Used Source Source Cite Cite

Go to Tool Page

evo-design/proto-language

View source

@articlelin2023esm2

@article{lin2023esm2,
  title={Evolutionary-scale prediction of atomic-level protein structure with a language model},
  author={Lin, Zeming and Akin, Halil and Rao, Roshan and Hie, Brian and Zhu, Zhongkai and Lu, Wenting and Smetanin, Nikita and Verkuil, Robert and Kabeli, Ori and Shmueli, Yaniv and others},
  journal={Science},
  volume={379},
  number={6637},
  pages={1123--1130},
  year={2023},
  publisher={American Association for the Advancement of Science},
  doi={10.1126/science.ade2574}
}

Copy citation

Constraint contributors

Forward ESM2 protein scoring via masked pseudo-log-likelihood.

API Reference

ConfigESM2PerplexityConfig Source

Configuration for ESM2 perplexity scoring (forward + gradient).

enum

default:"esm2_t33_650M_UR50D"

ESM2 model checkpoint to useOptions: esm2_t6_8M_UR50D, esm2_t12_35M_UR50D, esm2_t30_150M_UR50D, esm2_t33_650M_UR50D, esm2_t36_3B_UR50D, esm2_t48_15B_UR50D

number

required

Softmax temperature for ESM2 (fixed for this constraint, not varied per optimizer step).

boolean

default:"True"

Hard one-hot forward pass with soft-probability gradients.

string

default:"cuda"

Device for ESM2 execution, e.g. ‘cuda’ or ‘cuda:0’.

integer

AA positions per ESM2 forward pass. Lower if OOM, higher for throughput.

enum

default:"nll"

Return raw mean NLL by default, or ESM2 perplexity when set to ‘ppl’.Options: nll, ppl

number

default:"1.0"

Pre-scale raw logits before ESM2; gradients are scaled back by the same factor.

SequenceLogitBiasConfig

Declarative sequence-symbol bias (canonical 20-AA protein) added before ESM2.

Usage

python

from proto_language.core import Constraint
from proto_language.constraint import esm2_perplexity_constraint, ESM2PerplexityConfig

constraint = Constraint(
    inputs=[segment],
    function=esm2_perplexity_constraint,
    function_config=ESM2PerplexityConfig(
        # Configure parameters here
    ),
)

scores = constraint.evaluate()

Metadata

Property	Value
Key	`esm2-perplexity`
Function	`esm2_perplexity_constraint`
Category	`sequence_scoring`
Mode	`dual`
Uses GPU	`True`
Supported Types	`protein`

Language

Language Concepts

Language Guides

Constraints

Generators

Optimizers

ESM2 Perplexity

API Reference

Usage

Metadata

​API Reference

​Usage

​Metadata

API Reference

Usage

Metadata