sentence-transformers
PyTorch
setfit
Spanish
roberta
relation-classification
bert
biomedical
lexical semantics
bionlp
Instructions to use BSC-NLP4BIA/biomedical-semantic-relation-classifier-setfit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BSC-NLP4BIA/biomedical-semantic-relation-classifier-setfit with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BSC-NLP4BIA/biomedical-semantic-relation-classifier-setfit") 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] - setfit
How to use BSC-NLP4BIA/biomedical-semantic-relation-classifier-setfit with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("BSC-NLP4BIA/biomedical-semantic-relation-classifier-setfit") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6652669d2911e922fda165b7553dd62f782c7a3ca3a22496590641d6f575e81
- Size of remote file:
- 26.8 kB
- SHA256:
- 1796e873b6089da586fed84cd29365cd0d3c1470006a02da30fbd482d8cefd6d
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