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r1ck
/
vi-e5-large

Feature Extraction
Transformers
Safetensors
xlm-roberta
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use r1ck/vi-e5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use r1ck/vi-e5-large with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="r1ck/vi-e5-large")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("r1ck/vi-e5-large")
    model = AutoModel.from_pretrained("r1ck/vi-e5-large")
  • Notebooks
  • Google Colab
  • Kaggle
vi-e5-large
2.26 GB
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Ctrl+K
  • 1 contributor
History: 2 commits
r1ck's picture
r1ck
Upload 9 files
8ff5845 verified almost 2 years ago
  • 1_Pooling
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  • .gitattributes
    1.57 kB
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  • config.json
    690 Bytes
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  • model.safetensors
    2.24 GB
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  • modules.json
    387 Bytes
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  • sentence_bert_config.json
    57 Bytes
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  • sentencepiece.bpe.model
    5.07 MB
    xet
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  • special_tokens_map.json
    280 Bytes
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  • tokenizer.json
    17.1 MB
    xet
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  • tokenizer_config.json
    418 Bytes
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