Instructions to use Thomasboosinger/owlvit-base-patch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Thomasboosinger/owlvit-base-patch32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="Thomasboosinger/owlvit-base-patch32")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("Thomasboosinger/owlvit-base-patch32") model = AutoModelForZeroShotObjectDetection.from_pretrained("Thomasboosinger/owlvit-base-patch32") - Notebooks
- Google Colab
- Kaggle
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tags:
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- vision
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inference:
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# Model Card: OWL-ViT
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tags:
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- vision
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- zero-shot-object-detection
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inference: true
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# Model Card: OWL-ViT
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