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Gnartiel
/
vietnamese-sbert

Sentence Similarity
sentence-transformers
PyTorch
Transformers
roberta
feature-extraction
vietnamese
Model card Files Files and versions
xet
Community
1

Instructions to use Gnartiel/vietnamese-sbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Gnartiel/vietnamese-sbert with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Gnartiel/vietnamese-sbert")
    
    sentences = [
        "That is a happy person",
        "That is a happy dog",
        "That is a very happy person",
        "Today is a sunny day"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Transformers

    How to use Gnartiel/vietnamese-sbert with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("Gnartiel/vietnamese-sbert")
    model = AutoModel.from_pretrained("Gnartiel/vietnamese-sbert")
  • Notebooks
  • Google Colab
  • Kaggle
vietnamese-sbert
542 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 9 commits
Gnartiel's picture
Gnartiel
Add new SentenceTransformer model.
2f04c0d over 2 years ago
  • 1_Pooling
    Add new SentenceTransformer model. over 2 years ago
  • eval
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  • .gitattributes
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  • README.md
    3.9 kB
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  • added_tokens.json
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  • bpe.codes
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  • config.json
    797 Bytes
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  • config_sentence_transformers.json
    122 Bytes
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  • modules.json
    229 Bytes
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  • pytorch_model.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.FloatStorage"

    What is a pickle import?

    540 MB
    xet
    Add new SentenceTransformer model. over 2 years ago
  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
    965 Bytes
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  • tokenizer_config.json
    1.14 kB
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  • vocab.txt
    895 kB
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