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sentence-transformers
/
static-similarity-mrl-multilingual-v1

Sentence Similarity
sentence-transformers
ONNX
Safetensors
feature-extraction
Generated from Trainer
dataset_size:62698210
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results
Model card Files Files and versions
xet
Community
9

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
static-similarity-mrl-multilingual-v1
2.5 GB
Ctrl+K
Ctrl+K
  • 3 contributors
History: 15 commits
tomaarsen's picture
tomaarsen HF Staff
Update usage snippet to use organization name
b68f412 verified about 2 months ago
  • 0_StaticEmbedding
    Add new SentenceTransformer model almost 2 years ago
  • img
    Update figure -> Queries per Second to Sentences per Second almost 2 years ago
  • onnx
    Upload ONNX weights (#1) over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    149 kB
    Update usage snippet to use organization name about 2 months ago
  • config_sentence_transformers.json
    214 Bytes
    Update the min. ST version almost 2 years ago
  • modules.json
    141 Bytes
    Add new SentenceTransformer model almost 2 years ago
  • train.py
    14.5 kB
    Clarify why we call quit() almost 2 years ago