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nafisehNik
/
mt5-persian-summary

Summarization
Transformers
PyTorch
Persian
mt5
text2text-generation
Model card Files Files and versions
xet
Community
3

Instructions to use nafisehNik/mt5-persian-summary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use nafisehNik/mt5-persian-summary 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="nafisehNik/mt5-persian-summary")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("nafisehNik/mt5-persian-summary")
    model = AutoModelForSeq2SeqLM.from_pretrained("nafisehNik/mt5-persian-summary", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
mt5-persian-summary
1.21 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 10 commits
nafisehNik's picture
nafisehNik
Update README.md
b575560 over 2 years ago
  • .gitattributes
    1.34 kB
    initial commit almost 4 years ago
  • README.md
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    Update README.md over 2 years ago
  • config.json
    907 Bytes
    Update config.json almost 3 years ago
  • pytorch_model.bin
    1.2 GB
    xet
    add v1 almost 4 years ago
  • special_tokens_map.json
    65 Bytes
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  • spiece.model
    4.31 MB
    xet
    add v1 almost 4 years ago
  • tokenizer_config.json
    82 Bytes
    add v1 almost 4 years ago