Sentence Similarity
sentence-transformers
Safetensors
Japanese
modernbert
medical
japanese
ruri
embedding
text-embeddings-inference
Instructions to use genshiai-daichi/med-ruri-v3-70m-v2-from-ruri with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use genshiai-daichi/med-ruri-v3-70m-v2-from-ruri with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("genshiai-daichi/med-ruri-v3-70m-v2-from-ruri") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
| { | |
| "500": 0.3859062398415415, | |
| "1000": 0.4028251022017164, | |
| "1500": 0.4185390527584874, | |
| "2000": 0.43330019996953195, | |
| "2500": 0.44659083423553114, | |
| "3000": 0.4496575061053132, | |
| "3500": 0.4608934483931739, | |
| "4000": 0.4708195055654097, | |
| "4500": 0.4772869175667747, | |
| "5000": 0.48354546858168634, | |
| "5500": 0.48568894786407507, | |
| "6000": 0.48844015219854603, | |
| "6159": 0.4884732005383661 | |
| } |