Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
loss:MatryoshkaLoss
loss:CosineSimilarityLoss
chemistry
biology
drug-discovery
herbal
coconutdb
chembl34
selfies
drugs
molecules
compounds
Eval Results (legacy)
text-embeddings-inference
Instructions to use gbyuvd/chemembed-chemselfies with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use gbyuvd/chemembed-chemselfies with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("gbyuvd/chemembed-chemselfies") sentences = [ "[N] [C] [=N] [C] [=N] [C] [=C] [Ring1] [=Branch1] [S] [C] [=C] [C] [Branch1] [=Branch2] [C] [=C] [C] [=C] [C] [=C] [Ring1] [=Branch1] [=C] [C] [=C] [Ring1] [N] [Ring1] [#C]", "[C] [C] [C] [C] [C@H1] [Branch2] [#Branch2] [Branch2] [N] [C] [=Branch1] [C] [=O] [C@@H1] [C] [C] [C] [C] [N] [C] [=Branch1] [C] [=O] [C] [C] [C@H1] [Branch2] [=Branch1] [S] [N] [C] [=Branch1] [C] [=O] [C@H1] [Branch1] [#Branch2] [C] [C] [C] [N] [=C] [Branch1] [C] [N] [N] [N] [C] [=Branch1] [C] [=O] [C@H1] [Branch1] [#Branch1] [C] [C] [Branch1] [C] [C] [C] [N] [C] [=Branch1] [C] [=O] [C@H1] [Branch1] [#Branch1] [C] [C] [Branch1] [C] [C] [C] [N] [C] [=Branch1] [C] [=O] [C@H1] [Branch1] [=Branch2] [C] [C] [=C] [NH1] [C] [=N] [Ring1] [Branch1] [N] [C] [=Branch1] [C] [=O] [C@H1] [Branch1] [C] [N] [C] [C] [=C] [C] [=C] [C] [=C] [Ring1] [=Branch1] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [=Branch1] [C] [Branch1] [C] [C] [C] [C] [=Branch1] [C] [=O] [N] [C@H1] [Branch1] [#Branch1] [C] [C] [Branch1] [C] [C] [C] [C] [=Branch1] [C] [=O] [N] [Ring2] [=Branch1] [=C] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [C] [C] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [#Branch2] [C] [C] [C] [N] [=C] [Branch1] [C] [N] [N] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [C] [C] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [Branch2] [C] [C] [C] [=Branch1] [C] [=O] [O] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [Branch2] [C] [C] [C] [Branch1] [C] [N] [=O] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [#Branch1] [C] [C] [Branch1] [C] [C] [C] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [C] [C] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [Branch2] [C] [C] [C] [Branch1] [C] [N] [=O] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [Branch2] [C] [C] [C] [Branch1] [C] [N] [=O] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [C] [C] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [=Branch2] [C] [C] [=C] [NH1] [C] [=N] [Ring1] [Branch1] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [Ring1] [C] [O] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [#Branch1] [C] [C] [Branch1] [C] [N] [=O] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [#Branch2] [C] [C] [C] [N] [=C] [Branch1] [C] [N] [N] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [=Branch1] [C] [C] [C] [C] [N] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [#Branch1] [C] [C] [Branch1] [C] [C] [C] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [Branch1] [C] [C] [C] [C] [C] [=Branch1] [C] [=O] [N] [C@@H1] [Branch1] [Branch2] [C] [C] [C] [=Branch1] [C] [=O] [O] [C] [=Branch1] [C] [=O] [N] [C@H1] [Branch2] [Ring1] [Ring2] [C] [=Branch1] [C] [=O] [N] [C@H1] [Branch1] [=Branch1] [C] [Branch1] [C] [N] [=O] [C@@H1] [Branch1] [C] [C] [C] [C] [C@@H1] [Branch1] [C] [C] [C] [C]", "[C] [C] [=Branch1] [C] [=O] [N] [C@H1] [C@H1] [Branch2] [Ring2] [#Branch2] [O] [C@H1] [C@@H1] [Branch1] [C] [O] [C@@H1] [Branch1] [Ring1] [C] [O] [O] [C@@H1] [Branch2] [Ring1] [Branch1] [O] [C@H1] [C@H1] [Branch1] [C] [O] [C@@H1] [Branch1] [C] [O] [C@H1] [Branch1] [C] [O] [O] [C@@H1] [Ring1] [=Branch2] [C] [O] [C@@H1] [Ring2] [Ring1] [Branch1] [O] [O] [C@H1] [Branch1] [Ring1] [C] [O] [C@@H1] [Branch1] [C] [O] [C@@H1] [Ring2] [Ring1] [S] [O] [C@@H1] [O] [C@H1] [Branch1] [Ring1] [C] [O] [C@H1] [Branch1] [C] [O] [C@H1] [Branch1] [C] [O] [C@H1] [Ring1] [#Branch2] [O]", "[C] [C] [=C] [C] [=C] [C] [Branch2] [Ring1] [Ring1] [N] [C] [=Branch1] [C] [=O] [C] [O] [C] [=C] [C] [=C] [C] [Branch1] [C] [C] [=C] [Ring1] [#Branch1] [=C] [Ring2] [Ring1] [C]" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!