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:
- 5b09d8d6a3078ecc0a58f92642842a8c1e9ece790b1f3fc732c6bf397ff5e59e
- Size of remote file:
- 223 kB
- SHA256:
- b14546ae290d818ed45f198e7de5d82b78a2e60a1a30751a9f636af71be2967c
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