Sentence Similarity
sentence-transformers
Safetensors
English
gemma3_text
feature-extraction
text-embeddings-inference
clinical
medical
mimic-iii
contrastive-learning
ehr
Instructions to use gaspard-loeillot/embeddinggemma-mimic-infonce with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use gaspard-loeillot/embeddinggemma-mimic-infonce with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("gaspard-loeillot/embeddinggemma-mimic-infonce") 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
- Xet hash:
- d052c697673db3f4ebc9593ff1f2cbe0aa9c0218d1739773b474969a938212a6
- Size of remote file:
- 33.4 MB
- SHA256:
- d4931b1e84e7d009cb767e3f2ef1e35e1b1c14a535aeec93c1c0a90075623d33
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