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CardioEmbed-BGE-large-v1.5
richardyoung/CardioEmbed-BGE-large-v1.5
CardioEmbed-BGE-large-v1.5 is a sentence similarity model from richardyoung. Use it when you need a score for how close two texts are. It is set up for peft. The card lists the license as apache-2.0.
Domain-specialized cardiology text embeddings using LoRA-adapted BGE-large-v1.5
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At a glance
- Task
- Sentence Similarity
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Nov 24, 2025
- Updated
- Sep 26, 2026
- SHA
- 314f3da9
Base models
Model card
From the Hugging Face model README
CardioEmbed-BGE-large-v1.5
Domain-specialized cardiology text embeddings using LoRA-adapted BGE-large-v1.5
Part of a comparative study of 10 embedding architectures for clinical cardiology.
Performance
| Metric | Score |
|---|---|
| Separation Score | 0.314 |
Usage
from transformers import AutoModel, AutoTokenizer
from peft import PeftModel
base_model = AutoModel.from_pretrained("BAAI/bge-large-en-v1.5")
tokenizer = AutoTokenizer.from_pretrained("BAAI/bge-large-en-v1.5")
model = PeftModel.from_pretrained(base_model, "richardyoung/CardioEmbed-BGE-large-v1.5")
Training
- Training Data: 106,535 cardiology text pairs from medical textbooks
- Method: LoRA fine-tuning (r=16, alpha=32)
- Loss: Multiple Negatives Ranking Loss (InfoNCE)
Citation
@article{young2024comparative,
title={Comparative Analysis of LoRA-Adapted Embedding Models for Clinical Cardiology Text Representation},
author={Young, Richard J and Matthews, Alice M},
journal={arXiv preprint},
year={2024}
}
Built & maintained by Richard Young · DeepNeuro
- Task
- Sentence Similarity
- Library
- peft
- License
- apache-2.0
- Languages
- en
- Created
- Nov 24, 2025
- Updated
- Sep 26, 2026