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nanovdr
/
NanoVDR-M

Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
visual-document-retrieval
cross-modal-distillation
knowledge-distillation
nanovdr
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use nanovdr/NanoVDR-M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use nanovdr/NanoVDR-M with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("nanovdr/NanoVDR-M")
    
    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
NanoVDR-M
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
Ryenhails's picture
Ryenhails
Add blog post link
eddc041 verified about 2 months ago
  • 0_Transformer
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  • 1_Pooling
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  • 2_Dense
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  • 3_Dense
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  • .gitattributes
    1.57 kB
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  • README.md
    4.57 kB
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  • banner.png
    7.47 MB
    xet
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  • config.json
    612 Bytes
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  • config_sentence_transformers.json
    84 Bytes
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  • modules.json
    628 Bytes
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  • special_tokens_map.json
    125 Bytes
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  • tokenizer.json
    711 kB
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  • tokenizer_config.json
    1.22 kB
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  • vocab.txt
    232 kB
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