Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:247936
loss:CosineSimilarityLoss
text-embeddings-inference
Instructions to use lsy9874205/heal-protocol-embeddings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lsy9874205/heal-protocol-embeddings with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lsy9874205/heal-protocol-embeddings") sentences = [ "**Intervention costs**, including:\n - Medication costs\n - Provider time\n - Peer navigator time and expenses\n - Program administration", "4.2 Inclusion Criteria\n\nPatients must meet all of the following inclusion criteria to be eligible for the study:", "**MOUD Type**:\n - Methadone\n - Buprenorphine\n - Naltrexone", "Pregnancy (pregnant patients will be referred to specialized obstetric addiction services)" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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