Sentence Similarity
sentence-transformers
Japanese
English
feature-extraction
dense
Generated from Trainer
dataset_size:27195217
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
Instructions to use RikkaBotan/quantized-stable-static-embedding-fast-retrieval-mrl-bilingual-ja-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use RikkaBotan/quantized-stable-static-embedding-fast-retrieval-mrl-bilingual-ja-en with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("RikkaBotan/quantized-stable-static-embedding-fast-retrieval-mrl-bilingual-ja-en") 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

- Xet hash:
- c0bc24436c8d0f82e361367f84356ab15fee31151d34a8a4e6e4664c5fafd310
- Size of remote file:
- 216 kB
- SHA256:
- 710cff0b96eec171fd62b6dc3cc134531b148755878c83820f820aa10d12a4d5
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