Sentence Similarity
sentence-transformers
Japanese
feature-extraction
dense
Generated from Trainer
dataset_size:15098874
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
Instructions to use RikkaBotan/quantized-stable-static-embedding-fast-retrieval-mrl-ja 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-ja with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("RikkaBotan/quantized-stable-static-embedding-fast-retrieval-mrl-ja") 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:
- c3dd44d66656f3c552f4e88a134bf184bd8d0c5cac554c454fdfa73d2a99e01d
- Size of remote file:
- 724 kB
- SHA256:
- 9a041048155db5aad3010880943f95b632bb8754ff86e2c4a4f696697a4c2bce
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