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CapoCapped
/
T5Base

Summarization
Transformers
PyTorch
t5
text-generation
text-generation-inference
Model card Files Files and versions
xet
Community
1

Instructions to use CapoCapped/T5Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use CapoCapped/T5Base 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="CapoCapped/T5Base")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelWithLMHead
    
    tokenizer = AutoTokenizer.from_pretrained("CapoCapped/T5Base")
    model = AutoModelWithLMHead.from_pretrained("CapoCapped/T5Base")
  • Notebooks
  • Google Colab
  • Kaggle
T5Base
894 MB
Ctrl+K
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  • 1 contributor
History: 8 commits
CapoCapped's picture
CapoCapped
Create README.md
7692c95 about 4 years ago
  • .gitattributes
    1.22 kB
    initial commit about 4 years ago
  • README.md
    29 Bytes
    Create README.md about 4 years ago
  • config.json
    1.2 kB
    Upload config.json about 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    892 MB
    xet
    Upload pytorch_model.bin with git-lfs about 4 years ago
  • spiece.model
    792 kB
    xet
    Upload spiece.model with git-lfs about 4 years ago
  • tokenizer.json
    1.39 MB
    Upload tokenizer.json about 4 years ago