Instructions to use hf-internal-testing/tiny-random-owlvit-object-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-owlvit-object-detection 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-owlvit-object-detection")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-owlvit-object-detection") model = AutoModelForZeroShotObjectDetection.from_pretrained("hf-internal-testing/tiny-random-owlvit-object-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7089b1f3402eaa0d30fcc946bc2d00d9cb4d7e10c4a10875d48826fb851d964d
- Size of remote file:
- 14.4 MB
- SHA256:
- e6255a21f1ce7059d322d1978307ff54cbbac01ae21d604417bd6a69b5a78922
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