smiles-featurizers 1.0.0

A python library for extracting molecular SMILES embeddings from language models pre-trained with various objectives and/or architectures.

SMILES Featurizers

Extract SMILES embeddings from language models pre-trained with various objectives architectures.

Getting Started

pip install smiles-featurizers

Model List

Our released models are listed as following. You can import these models by using the smiles-featurizers package or using HuggingFace's Transformers.

Model	Type
shahrukhx01/smole-bert	Bert
shahrukhx01/smole-bert-mtr	Bert
shahrukhx01/smole-bart	Bart
shahrukhx01/muv2x-simcse-smole-bart	Simcse
shahrukhx01/siamese-smole-bert-muv-1x	SentenceTransformer

Use SMILES Featurizers

Bert Featurizer

from smiles_featurizers import BertFeaturizer

featurizer = BertFeaturizer("shahrukhx01/smole-bert")
embeddings = featurizer.embed(["CCC(C)(C)Br"])

Bart (Encoder) Featurizer

from smiles_featurizers import BartFeaturizer

featurizer = BartFeaturizer("shahrukhx01/smole-bart")
embeddings = featurizer.embed(["CCC(C)(C)Br"], embedder="encoder")

Bart (Decoder) Featurizer

from smiles_featurizers import BartFeaturizer

featurizer = BartFeaturizer("shahrukhx01/smole-bart")
embeddings = featurizer.embed(["CCC(C)(C)Br"], embedder="decoder")

SimCSE Featurizer

from smiles_featurizers import SimcseFeaturizer

featurizer = SimcseFeaturizer("shahrukhx01/mv2x-simcse-smole-bart")
embeddings = featurizer.embed(["CCC(C)(C)Br"])

SentenceTransformer Featurizer

from smiles_featurizers import SentenceTransformersFeaturizer

featurizer = SentenceTransformersFeaturizer("shahrukhx01/siamese-smole-bert-muv-1x")
embeddings = featurizer.embed(["CCC(C)(C)Br"])