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Alexhuou
/
embedder_model

Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:5700
loss:TripletLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Alexhuou/embedder_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Alexhuou/embedder_model with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Alexhuou/embedder_model")
    
    sentences = [
        "Statutes are often called ________ law.",
        "Calculate spin density on the central carbon atom of malonic acid radical (•CH(COOH)2) if the hyperfine value for the α-hydrogen atom is 21.9 G.",
        "Which of the following quotations best describes the central thesis of difference feminism?",
        "If a relevant variable is omitted from a regression equation, the consequences would be that:\n\ni) The standard errors would be biased\n\n\nii) If the excluded variable is uncorrelated with all of the included variables, all of\n\nthe slope coefficients will be inconsistent.\n\n\niii) If the excluded variable is uncorrelated with all of the included variables, the\n\nintercept coefficient will be inconsistent.\n\n\niv) If the excluded variable is uncorrelated with all of the included variables, all of\n\nthe slope and intercept coefficients will be consistent and unbiased but inefficient."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
embedder_model
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
Alexhuou's picture
Alexhuou
initial commit
be68bd3 verified 12 months ago
  • .gitattributes
    1.52 kB
    initial commit 12 months ago