sentence-transformers How to use officialthinkingstack/Sentence-Matcher-v0.3 with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("officialthinkingstack/Sentence-Matcher-v0.3")
sentences = [
"hypertension\nThe patient's primary diagnosis is hypertension, as stated in the visit note.\nBP medications\nThe patient is on BP medications which are used to treat hypertension.\nBP management\nThe visit note mentions follow-up on BP management, indicating ongoing treatment for hypertension.\nHTN\nHTN is the abbreviation for hypertension, which is the patient's diagnosed condition.\nBP was measured at 138/90\nThis blood pressure reading supports the diagnosis of hypertension as it is elevated.\nmonthly bp at home have been around that number or higher\nConsistently high blood pressure readings confirm the presence of hypertension.\nmost likely diagnosis for this patient is hypertension\nThe visit note explicitly states that hypertension is the most likely diagnosis.",
"Anemia, Unspecified",
"Essential (Primary) Hypertension",
"Dehydration"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
