Sentence Similarity
sentence-transformers
Safetensors
Japanese
modernbert
medical
japanese
ruri
embedding
text-embeddings-inference
Instructions to use genshiai-daichi/med-ruri-v3-310m-v2-from-med with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use genshiai-daichi/med-ruri-v3-310m-v2-from-med with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("genshiai-daichi/med-ruri-v3-310m-v2-from-med") 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
| { | |
| "5000": 0.5025078553632112, | |
| "5500": 0.4996305406859976, | |
| "6000": 0.5008372426317406, | |
| "6500": 0.5119956614356579, | |
| "7000": 0.5178643735591884, | |
| "7500": 0.5242606547265873, | |
| "8000": 0.5286588214529236, | |
| "8500": 0.5305105143721974, | |
| "9000": 0.5343248981447731, | |
| "9238": 0.5347855089896354 | |
| } |