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currentlyexhausted
/
flan-t5-summarizer

Summarization
Transformers
PyTorch
English
t5
text2text-generation
text-generation-inference
Model card Files Files and versions
xet
Community
1

Instructions to use currentlyexhausted/flan-t5-summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use currentlyexhausted/flan-t5-summarizer 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="currentlyexhausted/flan-t5-summarizer")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("currentlyexhausted/flan-t5-summarizer")
    model = AutoModelForSeq2SeqLM.from_pretrained("currentlyexhausted/flan-t5-summarizer")
  • Notebooks
  • Google Colab
  • Kaggle
flan-t5-summarizer
309 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
currentlyexhausted's picture
currentlyexhausted
Create README.md
021e47c about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • README.md
    134 Bytes
    Create README.md about 3 years ago
  • config.json
    1.53 kB
    Upload folder using huggingface_hub about 3 years ago
  • generation_config.json
    142 Bytes
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  • pytorch_model.bin
    308 MB
    xet
    Upload pytorch_model.bin with huggingface_hub about 3 years ago
  • special_tokens_map.json
    2.2 kB
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  • spiece.model
    792 kB
    xet
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  • tokenizer_config.json
    2.35 kB
    Upload folder using huggingface_hub about 3 years ago