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google
/
owlvit-base-patch32

Zero-Shot Object Detection
Transformers
PyTorch
Safetensors
owlvit
vision
Model card Files Files and versions
xet
Community
13

Instructions to use google/owlvit-base-patch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use google/owlvit-base-patch32 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-object-detection", model="google/owlvit-base-patch32")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection
    
    processor = AutoProcessor.from_pretrained("google/owlvit-base-patch32")
    model = AutoModelForZeroShotObjectDetection.from_pretrained("google/owlvit-base-patch32")
  • Notebooks
  • Google Colab
  • Kaggle
owlvit-base-patch32 / onnx
616 MB
Ctrl+K
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  • 7 contributors
History: 1 commit
optowo's picture
optowo
Adding ONNX file of this model
f08b536 verified about 2 years ago
  • config.json
    578 Bytes
    Adding ONNX file of this model about 2 years ago
  • merges.txt
    525 kB
    Adding ONNX file of this model about 2 years ago
  • model.onnx
    612 MB
    xet
    Adding ONNX file of this model about 2 years ago
  • preprocessor_config.json
    522 Bytes
    Adding ONNX file of this model about 2 years ago
  • special_tokens_map.json
    460 Bytes
    Adding ONNX file of this model about 2 years ago
  • tokenizer.json
    2.22 MB
    Adding ONNX file of this model about 2 years ago
  • tokenizer_config.json
    925 Bytes
    Adding ONNX file of this model about 2 years ago
  • vocab.json
    862 kB
    Adding ONNX file of this model about 2 years ago