Feature Extraction
sentence-transformers
Safetensors
English
modernbert
chemistry
cheminformatics
embeddings
text-embeddings-inference
Instructions to use SchwallerGroup/CheMatE-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use SchwallerGroup/CheMatE-v0 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("SchwallerGroup/CheMatE-v0") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
CheMatE
A ModernBERT-based embedding model for chemistry, producing embeddings for both molecular
(SMILES) and natural-language chemistry inputs. Fine-tuned from
SchwallerGroup/CheMatE-v0-MLM.
Usage
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("SchwallerGroup/CheMatE-v0")
emb = model.encode(["aspirin reduces inflammation", "CC(=O)Oc1ccccc1C(=O)O"], normalize_embeddings=True)
License
MIT.
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Model tree for SchwallerGroup/CheMatE-v0
Base model
SchwallerGroup/CheMatE-v0-MLM