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alfandy
/
bert2bert-batch2-lr5e-5-summarization

Transformers
Safetensors
encoder-decoder
text2text-generation
Model card Files Files and versions
xet
Community

Instructions to use alfandy/bert2bert-batch2-lr5e-5-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use alfandy/bert2bert-batch2-lr5e-5-summarization with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("alfandy/bert2bert-batch2-lr5e-5-summarization")
    model = AutoModelForSeq2SeqLM.from_pretrained("alfandy/bert2bert-batch2-lr5e-5-summarization", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
bert2bert-batch2-lr5e-5-summarization
999 MB
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  • 1 contributor
History: 2 commits
alfandy's picture
alfandy
add final models
94a9f72 verified over 2 years ago
  • .gitattributes
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  • README.md
    21 Bytes
    initial commit over 2 years ago
  • config.json
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  • generation_config.json
    281 Bytes
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  • model.safetensors
    999 MB
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  • special_tokens_map.json
    173 Bytes
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  • tokenizer_config.json
    1.34 kB
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  • training_args.bin
    4.98 kB
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  • vocab.txt
    230 kB
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