Instructions to use hf-internal-testing/tiny-random-Owlv2ForObjectDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Owlv2ForObjectDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="hf-internal-testing/tiny-random-Owlv2ForObjectDetection")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Owlv2ForObjectDetection") model = AutoModelForZeroShotObjectDetection.from_pretrained("hf-internal-testing/tiny-random-Owlv2ForObjectDetection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 666fc8ba6735625d646608dc0d8ae2c224a6a921181496981d40ec101cdba94b
- Size of remote file:
- 1.48 MB
- SHA256:
- 0b6e0d2bcd52f3751694036ed585f05097ef5cb2d625c86d121fd12ec9016047
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