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
- Xet hash:
- 049c93d347982a700e20138af8df7cfc20d0632cd92ac784e656f2b22eceb09c
- Size of remote file:
- 504 MB
- SHA256:
- 1f1fa545f1de84aa4aa9635850edc3a630a4a6fa1bdd2b38a1c1bb5a703db339
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.