Sentence Similarity
sentence-transformers
PyTorch
Safetensors
English
mpnet
feature-extraction
medical
biology
Instructions to use FremyCompany/BioLORD-2023-C with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use FremyCompany/BioLORD-2023-C with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("FremyCompany/BioLORD-2023-C") sentences = [ "bartonellosis", "cat scratch disease", "cat scratch wound", "tick-borne orbivirus fever", "cat fur" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [5, 5] - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7090876ad46448f3072cb6e8cd7633656d04572630f70d6280e7c52698918072
- Size of remote file:
- 438 MB
- SHA256:
- 6164f3a7476eaaeee4b7fa2d4dea655f8ca1927853b867d59fb9d66507f5d36f
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