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Cescofors75
/
baco-embeddings

Sentence Similarity
sentence-transformers
ONNX
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:68
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Cescofors75/baco-embeddings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Cescofors75/baco-embeddings with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Cescofors75/baco-embeddings")
    
    sentences = [
        "Pollo al curri rojo",
        "Vino blanco seco, ligero, refrescante, delicado y sauve. Con sabor ligero y poco denso, acostumbran a ser vinos jóvenes. Con aromas a cítricos, manzana verde, melocotón, piña e hinojo.",
        "Vinos rosados envejecidos en barrica, y también los vinos rosados elaborados a partir de Cabernet, Merlot o Syrah. Vinos rosados redondos, afrutados, de color intenso y sabor potente y sabroso. Con maceración de la piel.",
        "Vino blanco afrutado de medio cuerpo, con aromas a melocotón, piña, uva, fruta de la pasión, queroseno y flores. Ejemplos de variedades: los Verdejo de Rueda, Valencia Moscatell, los Malvasía de Canarias, los Riesling de Alsacia i Alemania. los Gerwüztraminer."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
baco-embeddings
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  • 1 contributor
History: 9 commits
Cescofors75's picture
Cescofors75
Upload fine_tuned_model.onnx
a262f7f verified over 1 year ago
  • 1_Pooling
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  • .gitattributes
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  • README.md
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  • config.json
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  • config_sentence_transformers.json
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  • model.onnx
    438 MB
    xet
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  • model.safetensors
    133 MB
    xet
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  • modules.json
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  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer_config.json
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  • vocab.txt
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