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T-Systems-onsite
/
mt5-small-sum-de-en-v2

Summarization
Transformers
PyTorch
Safetensors
German
English
multilingual
mt5
text2text-generation
Model card Files Files and versions
xet
Community
4

Instructions to use T-Systems-onsite/mt5-small-sum-de-en-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use T-Systems-onsite/mt5-small-sum-de-en-v2 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="T-Systems-onsite/mt5-small-sum-de-en-v2")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("T-Systems-onsite/mt5-small-sum-de-en-v2")
    model = AutoModelForSeq2SeqLM.from_pretrained("T-Systems-onsite/mt5-small-sum-de-en-v2")
  • Notebooks
  • Google Colab
  • Kaggle
mt5-small-sum-de-en-v2
2.41 GB
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  • 5 contributors
History: 15 commits
PhilipMay's picture
PhilipMay
Update README.md
ac9a09c verified about 2 years ago
  • .gitattributes
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    Adding `safetensors` variant of this model (#2) about 3 years ago
  • README.md
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  • config.json
    677 Bytes
    add first version with model files over 4 years ago
  • model.safetensors
    1.2 GB
    xet
    Adding `safetensors` variant of this model (#2) about 3 years ago
  • pytorch_model.bin
    1.2 GB
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  • special_tokens_map.json
    65 Bytes
    add first version with model files over 4 years ago
  • spiece.model
    4.31 MB
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  • tokenizer_config.json
    413 Bytes
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