Text Classification
sentence-transformers
PyTorch
Spanish
roberta
bert
biomedical
lexical semantics
bionlp
Instructions to use BSC-NLP4BIA/biomedical-term-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BSC-NLP4BIA/biomedical-term-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BSC-NLP4BIA/biomedical-term-classifier") 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
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README.md
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The model is prepared to classify medical entities among 21 classes, including diseases, medical procedures, symptoms, and drugs, among others. It still lacks some classes like body structures.
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## How to use
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This model is implemented as part of the KeyCARE library. Install first the keycare module to call the
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```bash
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python -m pip install keycare
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The model is prepared to classify medical entities among 21 classes, including diseases, medical procedures, symptoms, and drugs, among others. It still lacks some classes like body structures.
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## How to use
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This model is implemented as part of the KeyCARE library. Install first the keycare module to call the Transformer classifier:
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```bash
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python -m pip install keycare
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