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noname002
/
jina-embeddings-v5-text-nano-retrieval-mc4-vi

Sentence Similarity
Safetensors
GGUF
sentence-transformers
multilingual
llama.cpp
eurobert
embedding
llama-cpp
jina-embeddings-v5
feature-extraction
mteb
vllm
custom_code
Model card Files Files and versions
xet
Community

Instructions to use noname002/jina-embeddings-v5-text-nano-retrieval-mc4-vi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use noname002/jina-embeddings-v5-text-nano-retrieval-mc4-vi with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("noname002/jina-embeddings-v5-text-nano-retrieval-mc4-vi", trust_remote_code=True)
    
    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
jina-embeddings-v5-text-nano-retrieval-mc4-vi
282 MB
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  • 1 contributor
History: 2 commits
noname002's picture
noname002
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  • 1_Pooling
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  • .gitattributes
    1.52 kB
    initial commit 5 months ago
  • README.md
    9.22 kB
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  • config.json
    2.07 kB
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  • config_sentence_transformers.json
    299 Bytes
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  • configuration_eurobert.py
    12.1 kB
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  • model.safetensors
    279 MB
    xet
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  • modeling_eurobert.py
    49 kB
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  • modules.json
    429 Bytes
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  • sentence_bert_config.json
    241 Bytes
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  • tokenizer.json
    3.57 MB
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  • tokenizer_config.json
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