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longborn
/
attr2desc-bart-kw

Summarization
Transformers
PyTorch
Chinese
bart
text2text-generation
Eval Results (legacy)
Model card Files Files and versions
xet
Community
1

Instructions to use longborn/attr2desc-bart-kw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use longborn/attr2desc-bart-kw 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="longborn/attr2desc-bart-kw")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("longborn/attr2desc-bart-kw")
    model = AutoModelForSeq2SeqLM.from_pretrained("longborn/attr2desc-bart-kw")
  • Notebooks
  • Google Colab
  • Kaggle
attr2desc-bart-kw
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
longborn's picture
longborn
modify readme
9730cd2 about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • README.md
    271 Bytes
    modify readme about 3 years ago
  • added_tokens.json
    39 Bytes
    init about 3 years ago
  • config.json
    1.76 kB
    init about 3 years ago
  • pytorch_model.bin
    561 MB
    xet
    init about 3 years ago
  • special_tokens_map.json
    236 Bytes
    init about 3 years ago
  • tokenizer.json
    1.07 MB
    init about 3 years ago
  • tokenizer_config.json
    467 Bytes
    init about 3 years ago
  • vocab.txt
    259 kB
    init about 3 years ago