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ILT37
/
sbert_vietnamese

Feature Extraction
Transformers
Safetensors
roberta
Model card Files Files and versions
xet
Community

Instructions to use ILT37/sbert_vietnamese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ILT37/sbert_vietnamese with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="ILT37/sbert_vietnamese")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("ILT37/sbert_vietnamese")
    model = AutoModel.from_pretrained("ILT37/sbert_vietnamese")
  • Notebooks
  • Google Colab
  • Kaggle

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  • 1_Pooling
    Add new SentenceTransformer model. almost 2 years ago
  • .gitattributes
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  • README.md
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    Update README.md almost 2 years ago
  • added_tokens.json
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    Add new SentenceTransformer model. almost 2 years ago
  • bpe.codes
    1.14 MB
    Add new SentenceTransformer model. almost 2 years ago
  • config.json
    762 Bytes
    Add new SentenceTransformer model. almost 2 years ago
  • config_sentence_transformers.json
    205 Bytes
    Add new SentenceTransformer model. almost 2 years ago
  • model.safetensors
    540 MB
    xet
    Add new SentenceTransformer model. almost 2 years ago
  • modules.json
    229 Bytes
    Add new SentenceTransformer model. almost 2 years ago
  • sentence_bert_config.json
    53 Bytes
    Add new SentenceTransformer model. almost 2 years ago
  • special_tokens_map.json
    965 Bytes
    Add new SentenceTransformer model. almost 2 years ago
  • tokenizer_config.json
    1.14 kB
    Add new SentenceTransformer model. almost 2 years ago
  • vocab.txt
    895 kB
    Add new SentenceTransformer model. almost 2 years ago