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wxzhang
/
Zephyr-SeFT

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

Instructions to use wxzhang/Zephyr-SeFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use wxzhang/Zephyr-SeFT with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="wxzhang/Zephyr-SeFT")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("wxzhang/Zephyr-SeFT")
    model = AutoModel.from_pretrained("wxzhang/Zephyr-SeFT")
  • Notebooks
  • Google Colab
  • Kaggle
Zephyr-SeFT
28.4 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
wxzhang's picture
wxzhang
Upload tokenizer
9c1a759 verified over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    28 Bytes
    initial commit over 2 years ago
  • config.json
    629 Bytes
    Update config over 2 years ago
  • model-00001-of-00006.safetensors
    4.99 GB
    xet
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  • model-00002-of-00006.safetensors
    4.9 GB
    xet
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  • model-00003-of-00006.safetensors
    5 GB
    xet
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  • model-00004-of-00006.safetensors
    5 GB
    xet
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  • model-00005-of-00006.safetensors
    4.83 GB
    xet
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  • model-00006-of-00006.safetensors
    3.72 GB
    xet
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  • model.safetensors.index.json
    22.2 kB
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  • special_tokens_map.json
    551 Bytes
    Upload tokenizer over 2 years ago
  • tokenizer.json
    1.8 MB
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  • tokenizer_config.json
    1.39 kB
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