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")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("google/owlvit-base-patch16") model = AutoModelForZeroShotObjectDetection.from_pretrained("google/owlvit-base-patch16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Update preprocessor_config.json (#7)
- Update preprocessor_config.json (b623fb3ca0e45b39113ad8ce7ca3b02883d99e7e) Co-authored-by: Alara Dirik <adirik@users.noreply.huggingface.co>9ce716b
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Fix config bug (#6)
- Fix config bug (dfa29501e801fac0d96dfe80c6de1a5dbf424170) Co-authored-by: Alara Dirik <adirik@users.noreply.huggingface.co>209b820 -
Fix feature extractor resizing bug (#5)
- Fix feature extractor resizing bug (9cb3acb5f711ff82a0329b5f2084d8ac7135e4eb) Co-authored-by: Alara Dirik <adirik@users.noreply.huggingface.co>524231d
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Added model and processor
Alara Dirikfa9c4a0