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")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("rathi2023/owlvit-base-patch32") model = AutoModelForZeroShotObjectDetection.from_pretrained("rathi2023/owlvit-base-patch32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Training in progress, step 200
Verified signature8e8fb41 -
Training in progress, step 200
Verified signature5b89e29 -
Training in progress, step 200
Verified signature7d07d77
-
Training in progress, step 200
Verified signatureb74cced
-
Training in progress, step 200
Verified signaturec5b7679 -
Training in progress, step 200
Verified signature4686559
-
Training in progress, step 200
Verified signature442ee58