openprotein.embeddings.OpenProteinModel#

class openprotein.embeddings.OpenProteinModel(session, model_id, metadata=None)[source]#

Proprietary protein embedding models served by OpenProtein.

Examples

View specific model details (inc supported tokens) with the ? operator.

>>> import openprotein
>>> session = openprotein.connect(username="user", password="password")
>>> session.embedding.prot_seq?
Parameters:

  • session (APISession)

  • model_id (list[str] | str)

  • metadata (ModelMetadata | None)

__init__(session, model_id, metadata=None)#
Parameters:

  • session (APISession)

  • model_id (str)

  • metadata (ModelMetadata | None)

Methods

__init__(session, model_id[, metadata])

attn(sequences, **kwargs)

Compute attention embeddings for sequences using this model.

create(session, model_id[, default])

Create and return an instance of the appropriate EmbeddingModel subclass based on the model_id.

embed(sequences[, reduction])

Embed sequences using this model.

fit_gp(assay, properties, reduction[, name, ...])

Fit a Gaussian Process (GP) on an assay using this embedding model and hyperparameters.

fit_svd([sequences, assay, n_components, ...])

Fit an SVD on the embedding results of this model.

fit_umap([sequences, assay, n_components, ...])

Fit a UMAP on the embedding results of this model.

get_metadata()

Get model metadata for this model.

get_model()

Get the model_id(s) for this EmbeddingModel subclass.

logits(sequences, **kwargs)

Compute logit embeddings for sequences using this model.

Attributes

metadata

ModelMetadata for this model.

model_id