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linhha2705
/
multilingual-e5-nutrition

Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use linhha2705/multilingual-e5-nutrition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use linhha2705/multilingual-e5-nutrition with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("linhha2705/multilingual-e5-nutrition")
    
    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
multilingual-e5-nutrition
1.14 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
linhha2705's picture
linhha2705
Upload finetuned model
b591b09 verified about 1 year ago
  • 1_Pooling
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  • .gitattributes
    1.69 kB
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  • README.md
    179 kB
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  • config.json
    662 Bytes
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  • config_sentence_transformers.json
    205 Bytes
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  • metrics_comparison.png
    278 kB
    xet
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  • model.safetensors
    1.11 GB
    xet
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  • modules.json
    349 Bytes
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  • sentence_bert_config.json
    53 Bytes
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  • sentencepiece.bpe.model
    5.07 MB
    xet
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  • special_tokens_map.json
    964 Bytes
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  • tokenizer.json
    17.1 MB
    xet
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  • tokenizer_config.json
    1.18 kB
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  • training_progress.png
    232 kB
    xet
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