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grantpitt
/
autotagger

Feature Extraction
Transformers
PyTorch
vision-text-dual-encoder
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use grantpitt/autotagger with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="grantpitt/autotagger")
    # Load model directly
    from transformers import AutoProcessor, AutoModel
    
    processor = AutoProcessor.from_pretrained("grantpitt/autotagger")
    model = AutoModel.from_pretrained("grantpitt/autotagger")
  • Notebooks
  • Google Colab
  • Kaggle
autotagger
855 MB
Ctrl+K
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  • 1 contributor
History: 9 commits
grantpitt's picture
grantpitt
add model
7e560f0 almost 4 years ago
  • .gitattributes
    1.34 kB
    initial commit almost 4 years ago
  • config.json
    4.41 kB
    add model almost 4 years ago
  • merges.txt
    456 kB
    Upload merges.txt almost 4 years ago
  • preprocessor_config.json
    397 Bytes
    Upload preprocessor_config.json almost 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    852 MB
    xet
    add model almost 4 years ago
  • special_tokens_map.json
    280 Bytes
    Upload special_tokens_map.json almost 4 years ago
  • tokenizer.json
    2.11 MB
    Upload tokenizer.json almost 4 years ago
  • tokenizer_config.json
    435 Bytes
    Upload tokenizer_config.json almost 4 years ago
  • vocab.json
    798 kB
    Upload vocab.json almost 4 years ago