How to use cafierom/smiles_embedding_gemma_FT with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cafierom/smiles_embedding_gemma_FT") sentences = [ "C[C@H](CCCC(C)(C)O)[C@H]1CC[C@H]2[C@@H]3CC=C4C[C@@H](O)CC[C@]4(C)[C@H]3CC[C@]12C", "CC(C)n1c(CC[C@@H](O)C[C@@H](O)CC([O-])=O)c(c(c1C(=O)NCc1ccccn1)-c1ccccc1)-c1ccc(F)cc1", "Cc1cc(OCc2ccccc2)cc(C)c1\\C=C\\[C@@H]1C[C@@H](O)CC(=O)O1", "Cc1ccc(C2CC3CCC2C=C3)n1CC[C@@H]1C[C@@H](O)CC(=O)O1" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
