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swardiantara
/
vector-ordinal-max

Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use swardiantara/vector-ordinal-max with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use swardiantara/vector-ordinal-max with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("swardiantara/vector-ordinal-max")
    
    sentences = [
        "That is a happy person",
        "That is a happy dog",
        "That is a very happy person",
        "Today is a sunny day"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
vector-ordinal-max / eval
641 Bytes
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
swardiantara's picture
swardiantara
Scale L2 distance to [0.5, 2]
44028d4 about 1 year ago
  • similarity_evaluation_vector-ordinal-2_results.csv
    641 Bytes
    Scale L2 distance to [0.5, 2] about 1 year ago