sentence-transformers How to use cafierom/smiles_embedding_gemma_FT_full with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("cafierom/smiles_embedding_gemma_FT_full")
sentences = [
"O[C@H](C[C@H](O)\\C=C\\c1c2CCCC(Cc3ccc(Cl)cc3)c2nn1-c1ccc(F)cc1)CC([O-])=O",
"CC(C)c1sc(c(c1\\C=C\\[C@@H](O)C[C@@H](O)CC([O-])=O)-c1ccccc1)-c1ccccc1",
"C[C@H](CC\\C=C(/C)C(O)=O)[C@H]1CC[C@@]2(C)C3=CC[C@H]4C(C)(C)[C@@H](O)CC[C@]4(C)C3=CC[C@]12C",
"CCOC(=O)COc1ccc(CC=C)cc1OC"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
