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aikunu
/
all_MiniLM_L6_v2_moore

Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:8786
loss:CosineSimilarityLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use aikunu/all_MiniLM_L6_v2_moore with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use aikunu/all_MiniLM_L6_v2_moore with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("aikunu/all_MiniLM_L6_v2_moore")
    
    sentences = [
        "Mam ka paam n bãng yellã tiki-takɩ, n tõe n togs yãmb ye.",
        "Le creusement du puits est devenu profond mais on a pas encore atteint l'eau.",
        "Je n'ai pas compris exactement le problème pour pouvoir vous l'expliquer.",
        "Élisabeth, ta femme, te donnera un fil."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle

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  • modules.json
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  • sentence_bert_config.json
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  • vocab.txt
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