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jlee-larr
/
dynaflip-base

Zero-Shot Image Classification
Transformers
Safetensors
dynaflip
feature-extraction
custom_code
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use jlee-larr/dynaflip-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-image-classification", model="jlee-larr/dynaflip-base", trust_remote_code=True)
    pipe(
        "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png",
        candidate_labels=["animals", "humans", "landscape"],
    )
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("jlee-larr/dynaflip-base", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
dynaflip-base
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  • 2 contributors
History: 5 commits
jlee-larr's picture
jlee-larr
Update README.md
de6e49d verified about 16 hours ago
  • .gitattributes
    1.52 kB
    initial commit 5 days ago
  • README.md
    1.32 kB
    Update README.md about 16 hours ago
  • config.json
    736 Bytes
    Upload folder using huggingface_hub 5 days ago
  • configuration_dynaflip.py
    4.37 kB
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  • image_processing_dynaflip.py
    4.13 kB
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  • model.safetensors
    931 MB
    xet
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  • modeling_dynaflip.py
    22.4 kB
    Upload modeling_dynaflip.py with huggingface_hub 4 days ago
  • preprocessor_config.json
    484 Bytes
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  • processing_dynaflip.py
    3.05 kB
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  • special_tokens_map.json
    2.2 kB
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  • spiece.model
    792 kB
    xet
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  • tokenizer.json
    2.42 MB
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  • tokenizer_config.json
    20.8 kB
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