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]
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