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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1100edbe57ed3885d318ebd276ce00b7338c1f8b2498dcb63247b21a52b57c46
- Size of remote file:
- 613 MB
- SHA256:
- 7c393d464db060931cbe461fb0fad1225d249655f40e69117dd5e0045a53e828
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