Views
No views yet
adamleeit/pubmedbert-interop-mlm. It's specifically designed for generating embeddings for healthcare interoperability text.1from sentence_transformers import SentenceTransformer
2
3# Load model
4model = SentenceTransformer("adamleeit/pubmedbert-interop-sentence")
5
6# Generate embeddings for a single sentence or document
7embedding = model.encode("FHIR enables healthcare information exchange between systems.")
8
9# Generate embeddings for multiple documents
10documents = [
11 "FHIR is an HL7 standard for health information exchange.",
12 "SNOMED CT provides a comprehensive clinical terminology.",
13 "Interoperability frameworks enable secure data sharing between EHRs."
14]
15embeddings = model.encode(documents)adamleeit/pubmedbert-interop-mlm: The base masked language model from which this sentence transformer was derivedadamleeit/biolink-lg-interop-ner-model: Our NER model for identifying healthcare interoperability entities@misc{pubmedbert-interop-sentence,
author = {Lee AM},
title = {Healthcare Interoperability Sentence Transformer based on PubMedBERT},
year = {2025},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co/adamleeit/pubmedbert-interop-sentence}}
}