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heack
/
HeackMT5-ZhSum100k

Summarization
Transformers
PyTorch
Chinese
mt5
text2text-generation
mT5
Model card Files Files and versions
xet
Community
5

Instructions to use heack/HeackMT5-ZhSum100k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use heack/HeackMT5-ZhSum100k with Transformers:

    # Use a pipeline as a high-level helper
    # Warning: Pipeline type "summarization" is no longer supported in transformers v5.
    # You must load the model directly (see below) or downgrade to v4.x with:
    # 'pip install "transformers<5.0.0'
    from transformers import pipeline
    
    pipe = pipeline("summarization", model="heack/HeackMT5-ZhSum100k")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("heack/HeackMT5-ZhSum100k")
    model = AutoModelForSeq2SeqLM.from_pretrained("heack/HeackMT5-ZhSum100k")
  • Notebooks
  • Google Colab
  • Kaggle
HeackMT5-ZhSum100k
2.33 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 11 commits
heack's picture
heack
Update README.md
883aac5 verified over 1 year ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • README.md
    9.02 kB
    Update README.md over 1 year ago
  • config.json
    751 Bytes
    initial publish almost 3 years ago
  • license_pay.jpeg
    121 Bytes
    Create license_pay.jpeg over 1 year ago
  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    2.33 GB
    xet
    initial publish almost 3 years ago
  • special_tokens_map.json
    65 Bytes
    initial publish almost 3 years ago
  • spiece.model
    4.31 MB
    xet
    initial publish almost 3 years ago
  • tokenizer_config.json
    375 Bytes
    initial publish almost 3 years ago