Instructions to use rathi2023/owlvit-base-patch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rathi2023/owlvit-base-patch32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="rathi2023/owlvit-base-patch32")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("rathi2023/owlvit-base-patch32") model = AutoModelForZeroShotObjectDetection.from_pretrained("rathi2023/owlvit-base-patch32") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- Apr16_20-32-20_e94151ae2d81
- Apr17_05-59-08_7a388677337a
- Apr17_19-00-51_4d3994b3e917
- Apr18_00-02-56_9b1f57022808
- Apr20_03-18-36_800ee83d46ca
- Apr20_04-54-40_c87bc485f4e5
- Apr20_04-59-43_c87bc485f4e5
- Apr20_05-05-58_c87bc485f4e5
- Apr20_05-16-19_c87bc485f4e5
- Apr20_06-09-25_e8a9fe3c62aa
- Apr20_06-13-26_e8a9fe3c62aa