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2dameneko
/
neko-pickscore

Zero-Shot Image Classification
Transformers
Safetensors
English
clip
pickscore
image-scoring
aesthetic
custom-taste
Model card Files Files and versions
xet
Community

Instructions to use 2dameneko/neko-pickscore with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use 2dameneko/neko-pickscore with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-image-classification", model="2dameneko/neko-pickscore")
    pipe(
        "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png",
        candidate_labels=["animals", "humans", "landscape"],
    )
    # Load model directly
    from transformers import AutoProcessor, AutoModelForZeroShotImageClassification
    
    processor = AutoProcessor.from_pretrained("2dameneko/neko-pickscore")
    model = AutoModelForZeroShotImageClassification.from_pretrained("2dameneko/neko-pickscore")
  • Notebooks
  • Google Colab
  • Kaggle
neko-pickscore
1.98 GB
Ctrl+K
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  • 1 contributor
History: 5 commits
2dameneko's picture
2dameneko
Update README.md
fbe675b verified about 16 hours ago
  • .gitattributes
    1.52 kB
    initial commit about 17 hours ago
  • README.md
    3.48 kB
    Update README.md about 16 hours ago
  • config.json
    1.26 kB
    Upload 8 files about 17 hours ago
  • merges.txt
    525 kB
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  • model.safetensors
    1.97 GB
    xet
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  • preprocessor_config.json
    532 Bytes
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  • special_tokens_map.json
    618 Bytes
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  • tokenizer.json
    3.64 MB
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  • tokenizer_config.json
    805 Bytes
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  • vocab.json
    862 kB
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