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NlpHUST
/
t5-small-vi-summarization

Transformers
PyTorch
JAX
t5
text2text-generation
text-generation-inference
Model card Files Files and versions
xet
Community
1

Instructions to use NlpHUST/t5-small-vi-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use NlpHUST/t5-small-vi-summarization with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("NlpHUST/t5-small-vi-summarization")
    model = AutoModelForSeq2SeqLM.from_pretrained("NlpHUST/t5-small-vi-summarization")
  • Notebooks
  • Google Colab
  • Kaggle
t5-small-vi-summarization
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  • 3 contributors
History: 8 commits
patrickvonplaten's picture
patrickvonplaten
upload flax model
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  • .gitattributes
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  • README.md
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  • config.json
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  • flax_model.msgpack
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  • pytorch_model.bin

    Detected Pickle imports (3)

    • "torch.FloatStorage",
    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    1.2 GB
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  • special_tokens_map.json
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  • spiece.model
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  • tokenizer_config.json
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