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shtilev
/
medical_embedded_v2

Sentence Similarity
sentence-transformers
Safetensors
distilbert
feature-extraction
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use shtilev/medical_embedded_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use shtilev/medical_embedded_v2 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("shtilev/medical_embedded_v2")
    
    sentences = [
        "The weather is lovely today.",
        "It's so sunny outside!",
        "He drove to the stadium."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [3, 3]
  • Notebooks
  • Google Colab
  • Kaggle
medical_embedded_v2
544 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
shtilev's picture
shtilev
Upload folder using huggingface_hub
c8ffa6f verified about 1 year ago
  • 1_Pooling
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  • 2_Dense
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  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    2.24 kB
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  • config.json
    501 Bytes
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  • config_sentence_transformers.json
    205 Bytes
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  • model.safetensors
    539 MB
    xet
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  • modules.json
    341 Bytes
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  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
    695 Bytes
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  • tokenizer.json
    2.92 MB
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  • tokenizer_config.json
    1.3 kB
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  • vocab.txt
    996 kB
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