Sentence Similarity
sentence-transformers
English
feature-extraction
dense
clinical-trials
biomedical
embeddings
contrastive-learning
patient-population
Instructions to use Ontologer/PACT-ClinicalTrials-Pop-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Ontologer/PACT-ClinicalTrials-Pop-256 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Ontologer/PACT-ClinicalTrials-Pop-256") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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