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microsoft
/
ssr-base

Summarization
Transformers
PyTorch
English
t5
text2text-generation
text-generation-inference
Model card Files Files and versions
xet
Community
2

Instructions to use microsoft/ssr-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use microsoft/ssr-base 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="microsoft/ssr-base")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("microsoft/ssr-base")
    model = AutoModelForSeq2SeqLM.from_pretrained("microsoft/ssr-base")
  • Notebooks
  • Google Colab
  • Kaggle
ssr-base
892 MB
Ctrl+K
Ctrl+K
  • 3 contributors
History: 4 commits
joaogante's picture
joaogante
Adding generation config file(s)
716ca30 over 3 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • README.md
    244 Bytes
    Create README.md over 4 years ago
  • config.json
    682 Bytes
    upload over 4 years ago
  • generation_config.json
    286 Bytes
    Adding generation config file(s) over 3 years ago
  • pytorch_model.bin
    892 MB
    xet
    upload over 4 years ago
  • special_tokens_map.json
    1.79 kB
    upload over 4 years ago
  • spiece.model
    792 kB
    xet
    upload over 4 years ago
  • tokenizer_config.json
    1.86 kB
    upload over 4 years ago