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albertus-sussex
/
veriscrape-book-test-sbert-bs128_lr0.0002_ep5_cosine_snTrue_spFalse_hn1

Sentence Similarity
sentence-transformers
Safetensors
new
feature-extraction
Generated from Trainer
dataset_size:84524
loss:AttributeTripletLoss
custom_code
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use albertus-sussex/veriscrape-book-test-sbert-bs128_lr0.0002_ep5_cosine_snTrue_spFalse_hn1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use albertus-sussex/veriscrape-book-test-sbert-bs128_lr0.0002_ep5_cosine_snTrue_spFalse_hn1 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("albertus-sussex/veriscrape-book-test-sbert-bs128_lr0.0002_ep5_cosine_snTrue_spFalse_hn1", trust_remote_code=True)
    
    sentences = [
        "Don Piper",
        "Tommy Nelson",
        "Kate Walbert",
        "publisher",
        "author"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [5, 5]
  • Notebooks
  • Google Colab
  • Kaggle
veriscrape-book-test-sbert-bs128_lr0.0002_ep5_cosine_snTrue_spFalse_hn1 / 1_Pooling
Ctrl+K
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  • 1 contributor
History: 1 commit
albertus-sussex's picture
albertus-sussex
Add new SentenceTransformer model
8a2043e verified over 1 year ago
  • config.json
    296 Bytes
    Add new SentenceTransformer model over 1 year ago