Sentence Similarity
sentence-transformers
PyTorch
Safetensors
English
mpnet
feature-extraction
medical
biology
text-embeddings-inference
Instructions to use FremyCompany/BioLORD-2023 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use FremyCompany/BioLORD-2023 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("FremyCompany/BioLORD-2023") 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
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# FremyCompany/BioLORD-2023
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This model was trained using BioLORD, a new pre-training strategy for producing meaningful representations for clinical sentences and biomedical concepts.
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| 🙏 If you are able to, please help me [fund my open research](https://gofund.me/1f2d6803). 🙏 Thank you for your generosity! 🤗 |
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# FremyCompany/BioLORD-2023
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This model was trained using BioLORD, a new pre-training strategy for producing meaningful representations for clinical sentences and biomedical concepts.
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