Instructions to use hf-internal-testing/tiny-random-GroundingDinoForObjectDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GroundingDinoForObjectDetection 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-GroundingDinoForObjectDetection")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-GroundingDinoForObjectDetection") model = AutoModelForZeroShotObjectDetection.from_pretrained("hf-internal-testing/tiny-random-GroundingDinoForObjectDetection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 642430a595bf485c01f16bf7e655f6cb7ac575d3ff33c74222c7f5b317d00ba3
- Size of remote file:
- 32.4 MB
- SHA256:
- 7fc12021bcf95e7173467694b209d9fa4bcd60fd0badbcd8106283df95f01c50
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