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NetherQuartz
/
paraphrase-MiniLM-tokipona

Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:82069
loss:MSELoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use NetherQuartz/paraphrase-MiniLM-tokipona with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use NetherQuartz/paraphrase-MiniLM-tokipona with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("NetherQuartz/paraphrase-MiniLM-tokipona")
    
    sentences = [
        "Kendi kendine yardım etsen Tanrı da sana yardımcı olur.",
        "nasin sina li pona seme?",
        "ona li jan sona.",
        "o pana e pona tawa sama sina la mama sewi li pana e pona tawa sina."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
paraphrase-MiniLM-tokipona / eval
792 Bytes
Ctrl+K
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  • 1 contributor
History: 1 commit
NetherQuartz's picture
NetherQuartz
End of training
fc2b1d9 verified about 2 months ago
  • mse_evaluation_eval_data_results.csv
    278 Bytes
    End of training about 2 months ago
  • translation_evaluation_eval_data_results.csv
    514 Bytes
    End of training about 2 months ago