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AntoineBlanot
/
t5-uNLU

Feature Extraction
Transformers
PyTorch
t5
Model card Files Files and versions
xet
Community
1

Instructions to use AntoineBlanot/t5-uNLU with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use AntoineBlanot/t5-uNLU with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="AntoineBlanot/t5-uNLU")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("AntoineBlanot/t5-uNLU")
    model = AutoModel.from_pretrained("AntoineBlanot/t5-uNLU", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
t5-uNLU
Ctrl+K
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  • 2 contributors
History: 4 commits
AntoineBlanot's picture
AntoineBlanot
Update config.json
fe64c0a about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • config.json
    873 Bytes
    Update config.json about 3 years ago
  • pytorch_model-00001-of-00005.bin
    4.45 GB
    xet
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  • pytorch_model-00002-of-00005.bin
    5 GB
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  • pytorch_model-00003-of-00005.bin
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  • pytorch_model-00004-of-00005.bin
    4.63 GB
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  • pytorch_model-00005-of-00005.bin
    3.65 GB
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  • pytorch_model.bin.index.json
    24 kB
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  • special_tokens_map.json
    2.2 kB
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  • tokenizer.json
    2.42 MB
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  • tokenizer_config.json
    2.35 kB
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