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
- Xet hash:
- a499c2edc2b89c23c7e03c931b2fe6b5d062a76909b402444f5a36969e09dd65
- Size of remote file:
- 611 MB
- SHA256:
- de5c19e5c16a57507e7e3f979e59b4e9ea80e3e1804835f37c07748534f40222
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