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hiepnh
/
ta-p-biencoder

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

Instructions to use hiepnh/ta-p-biencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use hiepnh/ta-p-biencoder with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="hiepnh/ta-p-biencoder")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("hiepnh/ta-p-biencoder")
    model = AutoModel.from_pretrained("hiepnh/ta-p-biencoder")
  • Notebooks
  • Google Colab
  • Kaggle
ta-p-biencoder
445 MB
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  • 1 contributor
History: 11 commits
hiepnh's picture
hiepnh
Upload config.json with huggingface_hub
b3bf3e5 verified over 2 years ago
  • 1_Pooling
    Upload 1_Pooling/config.json with huggingface_hub over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • config.json
    724 Bytes
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  • config_sentence_transformers.json
    117 Bytes
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  • model.safetensors
    445 MB
    xet
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  • modules.json
    229 Bytes
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  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
    125 Bytes
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  • tokenizer_config.json
    1.43 kB
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  • vocab.txt
    236 kB
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