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mrm8488
/
bert2bert_shared-german-finetuned-summarization

Summarization
Transformers
PyTorch
Safetensors
German
encoder-decoder
text2text-generation
news
Model card Files Files and versions
xet
Community
5

Instructions to use mrm8488/bert2bert_shared-german-finetuned-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

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  • Transformers

    How to use mrm8488/bert2bert_shared-german-finetuned-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="mrm8488/bert2bert_shared-german-finetuned-summarization")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("mrm8488/bert2bert_shared-german-finetuned-summarization")
    model = AutoModelForSeq2SeqLM.from_pretrained("mrm8488/bert2bert_shared-german-finetuned-summarization")
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Max summary length?

#4 opened over 3 years ago by
Melchior-Blank

Truncated results on some text

4
#3 opened almost 4 years ago by
Sergej

Slightly better results than the reported results and some questions about the model

#2 opened almost 4 years ago by
JingFan

This fine tuned model is not working

👍 3
4
#1 opened almost 4 years ago by
SudhanshuBlaze
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