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transformer3
/
H2-keywordextractor

Summarization
Transformers
PyTorch
Enawené-Nawé
bart
text2text-generation
Trained with AutoTrain
Model card Files Files and versions
xet
Community
4

Instructions to use transformer3/H2-keywordextractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use transformer3/H2-keywordextractor 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="transformer3/H2-keywordextractor")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("transformer3/H2-keywordextractor")
    model = AutoModelForSeq2SeqLM.from_pretrained("transformer3/H2-keywordextractor")
  • Notebooks
  • Google Colab
  • Kaggle
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Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

What is the input character length limit?

#4 opened about 2 years ago by
strangekey

remove invalid language tag

#3 opened over 2 years ago by
julien-c

How do we make a request? Result from inference API and inference endpoint are different

#2 opened over 2 years ago by
rafa9

Adding `safetensors` variant of this model

#1 opened about 3 years ago by
SFconvertbot
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