Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
feature-extraction
text-embeddings-inference
Instructions to use champ7/LOINC_CROSS_ENCODER1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use champ7/LOINC_CROSS_ENCODER1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("champ7/LOINC_CROSS_ENCODER1") 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
d179881 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:11acfd476d36d457f3354aef39e503155cbcd3dfbf8a6c335ec4ecaca87ee437
size 33385007
|