Sentence Similarity
sentence-transformers
ONNX
Safetensors
feature-extraction
Generated from Trainer
dataset_size:62698210
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results
Instructions to use sentence-transformers/static-similarity-mrl-multilingual-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sentence-transformers/static-similarity-mrl-multilingual-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/static-similarity-mrl-multilingual-v1") sentences = [ "A man is jumping unto his filthy bed.", "A man is ouside near the beach.", "The bed is dirty.", "The man is on the moon." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Commit History
Link to the blogpost 6501536 verified
Add link to the other static model 75b2c50
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Mention 0 active parameters, 100-400x faster e60353d
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Update figure -> Queries per Second to Sentences per Second db5fc0a
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Clarify why we call quit() bb98c75
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Also link to the training script b475b47
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Add evaluation results to repository 64f74e2
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Update training script to separate dataset loading & training a4605b3
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Reflect that JW300 was removed f9c9b72
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Update the min. ST version 6e99faa
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