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Perry-DLC
/
upy-u2t02-simcse

Sentence Similarity
sentence-transformers
Safetensors
English
bert
simcse
feature-extraction
contrastive-learning
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Perry-DLC/upy-u2t02-simcse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Perry-DLC/upy-u2t02-simcse with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Perry-DLC/upy-u2t02-simcse")
    
    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
upy-u2t02-simcse
439 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
Perry-DLC's picture
Perry-DLC
Update README.md
7324759 verified 6 days ago
  • 1_Pooling
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  • 2_Normalize
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  • .gitattributes
    1.52 kB
    initial commit 7 days ago
  • README.md
    3.79 kB
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  • config.json
    746 Bytes
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  • config_sentence_transformers.json
    284 Bytes
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  • model.safetensors
    438 MB
    xet
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  • modules.json
    413 Bytes
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  • sentence_bert_config.json
    241 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    539 Bytes
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