Instructions to use google/owlvit-base-patch16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/owlvit-base-patch16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="google/owlvit-base-patch16")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("google/owlvit-base-patch16") model = AutoModelForZeroShotObjectDetection.from_pretrained("google/owlvit-base-patch16") - Notebooks
- Google Colab
- Kaggle
File size: 775 Bytes
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"bos_token": {
"__type": "AddedToken",
"content": "<|startoftext|>",
"lstrip": false,
"normalized": true,
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"single_word": false
},
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"eos_token": {
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"content": "<|endoftext|>",
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"errors": "replace",
"model_max_length": 16,
"name_or_path": "openai/clip-vit-base-patch32",
"pad_token": "!",
"processor_class": "OwlViTProcessor",
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