Instructions to use mayank0621/owlvit-base-patch32_FT_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mayank0621/owlvit-base-patch32_FT_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="mayank0621/owlvit-base-patch32_FT_cppe5")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("mayank0621/owlvit-base-patch32_FT_cppe5") model = AutoModelForZeroShotObjectDetection.from_pretrained("mayank0621/owlvit-base-patch32_FT_cppe5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81b4b0edbbe6295b65f289f3409cac771bba830c24bb02db69e71d319dc0cdf6
- Size of remote file:
- 4.67 kB
- SHA256:
- 703d693b9c57c436166bc6a36c373ecf5905607dd1236f86533c3930cfdac8f6
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