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kadasterdst
/
t5-pretrained

Feature Extraction
Transformers
PyTorch
google-tensorflow TensorFlow
t5
generated_from_keras_callback
Model card Files Files and versions
xet
Community
1

Instructions to use kadasterdst/t5-pretrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use kadasterdst/t5-pretrained with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="kadasterdst/t5-pretrained")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("kadasterdst/t5-pretrained")
    model = AutoModel.from_pretrained("kadasterdst/t5-pretrained")
  • Notebooks
  • Google Colab
  • Kaggle
t5-pretrained
122 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 16 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
d258f75 almost 3 years ago
  • .gitattributes
    1.48 kB
    initial commit over 3 years ago
  • README.md
    861 Bytes
    Upload model over 3 years ago
  • config.json
    741 Bytes
    Upload model about 3 years ago
  • model.safetensors
    36 MB
    xet
    Adding `safetensors` variant of this model almost 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    36.1 MB
    xet
    Upload model about 3 years ago
  • special_tokens_map.json
    2.2 kB
    Upload tokenizer about 3 years ago
  • tf_model.h5
    49.5 MB
    xet
    Upload model about 3 years ago
  • tokenizer.json
    410 kB
    Upload tokenizer about 3 years ago
  • tokenizer_config.json
    2.54 kB
    Upload tokenizer about 3 years ago