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asaakyan
/
gutenberg_authorship

Sentence Similarity
sentence-transformers
Safetensors
roberta
feature-extraction
Generated from Trainer
dataset_size:4415131
loss:TripletLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • sentence-transformers

    How to use asaakyan/gutenberg_authorship with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("asaakyan/gutenberg_authorship")
    
    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
gutenberg_authorship / 1_Pooling
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
asaakyan's picture
asaakyan
Upload model files
9d884e1 over 1 year ago
  • config.json
    296 Bytes
    Upload model files over 1 year ago