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AlgorithmicResearchGroup
/
led_base_16384_billsum_summarization

Summarization
Transformers
PyTorch
Safetensors
English
led
text2text-generation
Eval Results (legacy)
Model card Files Files and versions
xet
Community
5

Instructions to use AlgorithmicResearchGroup/led_base_16384_billsum_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use AlgorithmicResearchGroup/led_base_16384_billsum_summarization 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="AlgorithmicResearchGroup/led_base_16384_billsum_summarization")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("AlgorithmicResearchGroup/led_base_16384_billsum_summarization")
    model = AutoModelForSeq2SeqLM.from_pretrained("AlgorithmicResearchGroup/led_base_16384_billsum_summarization")
  • Notebooks
  • Google Colab
  • Kaggle
led_base_16384_billsum_summarization
7.36 GB
Ctrl+K
Ctrl+K
  • 4 contributors
History: 15 commits
ArtifactAI
Update README.md
bd70b7d about 3 years ago
  • .gitattributes
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  • tokenizer.json
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  • vocab.json
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