Sentence Similarity
PEFT
Safetensors
sentence-transformers
English
medical
cardiology
embeddings
domain-adaptation
lora
Instructions to use richardyoung/CardioEmbed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use richardyoung/CardioEmbed with PEFT:
Task type is invalid.
- sentence-transformers
How to use richardyoung/CardioEmbed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("richardyoung/CardioEmbed") 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
File size: 133 Bytes
fabf094 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:00bc7e8d1c2c18e5ced697f8b4beb4e4e8f4285180ffbe6b51d1b46d12cc9a75
size 11423213
|