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Jarbas
/
m2v-256-roberta-base-ca-cased-sts

Model2Vec
Safetensors
sentence-transformers
Catalan
embeddings
static-embeddings
Model card Files Files and versions
xet
Community

Instructions to use Jarbas/m2v-256-roberta-base-ca-cased-sts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Model2Vec

    How to use Jarbas/m2v-256-roberta-base-ca-cased-sts with Model2Vec:

    from model2vec import StaticModel
    
    model = StaticModel.from_pretrained("Jarbas/m2v-256-roberta-base-ca-cased-sts")
  • sentence-transformers

    How to use Jarbas/m2v-256-roberta-base-ca-cased-sts with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Jarbas/m2v-256-roberta-base-ca-cased-sts")
    
    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
m2v-256-roberta-base-ca-cased-sts
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  • 1 contributor
History: 2 commits
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Jarbas
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2fb4f60 verified 12 months ago
  • .gitattributes
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    initial commit 12 months ago
  • README.md
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  • config.json
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  • model.safetensors
    26.6 MB
    xet
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  • modules.json
    278 Bytes
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  • tokenizer.json
    3.8 MB
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