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maanaar
/
clip-vit-large-patch14-128

Zero-Shot Image Classification
Transformers
Safetensors
clip
Model card Files Files and versions
xet
Community

Instructions to use maanaar/clip-vit-large-patch14-128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use maanaar/clip-vit-large-patch14-128 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-image-classification", model="maanaar/clip-vit-large-patch14-128")
    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("maanaar/clip-vit-large-patch14-128")
    model = AutoModelForZeroShotImageClassification.from_pretrained("maanaar/clip-vit-large-patch14-128")
  • Notebooks
  • Google Colab
  • Kaggle
clip-vit-large-patch14-128
1.72 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 9 commits
maanaar's picture
maanaar
Upload processor with 128 tokens
02988d0 verified 9 months ago
  • .gitattributes
    1.52 kB
    initial commit 9 months ago
  • README.md
    5.17 kB
    128 tokens 9 months ago
  • config.json
    1.17 kB
    128 tokens 9 months ago
  • merges.txt
    525 kB
    128 tokens 9 months ago
  • model.safetensors
    1.71 GB
    xet
    128 tokens 9 months ago
  • preprocessor_config.json
    504 Bytes
    Added processor with 128 tokens 9 months ago
  • special_tokens_map.json
    588 Bytes
    128 tokens 9 months ago
  • tokenizer.json
    3.64 MB
    Added processor with 128 tokens 9 months ago
  • tokenizer_config.json
    775 Bytes
    Upload processor with 128 tokens 9 months ago
  • vocab.json
    862 kB
    Upload processor with 128 tokens 9 months ago