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vaguely-happy
/
Swift_GODEL

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

Instructions to use vaguely-happy/Swift_GODEL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use vaguely-happy/Swift_GODEL 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="vaguely-happy/Swift_GODEL")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("vaguely-happy/Swift_GODEL")
    model = AutoModelForSeq2SeqLM.from_pretrained("vaguely-happy/Swift_GODEL")
  • Notebooks
  • Google Colab
  • Kaggle
Swift_GODEL
894 MB
Ctrl+K
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  • 1 contributor
History: 8 commits
vaguely-happy's picture
vaguely-happy
Update README.md
0d53938 over 3 years ago
  • .gitattributes
    1.48 kB
    initial commit over 3 years ago
  • README.md
    71 Bytes
    Update README.md over 3 years ago
  • config.json
    1.5 kB
    Upload T5ForConditionalGeneration over 3 years ago
  • generation_config.json
    142 Bytes
    Upload T5ForConditionalGeneration over 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    892 MB
    xet
    Upload T5ForConditionalGeneration over 3 years ago
  • special_tokens_map.json
    2.2 kB
    Upload tokenizer over 3 years ago
  • tokenizer.json
    2.42 MB
    Upload tokenizer over 3 years ago
  • tokenizer_config.json
    2.37 kB
    Upload tokenizer over 3 years ago