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:
- 1f8be845328ece55da3f1a14bb85bd197baf584e0b8c2337cf5702fb09f37922
- Size of remote file:
- 31.1 MB
- SHA256:
- efeb11a94e9e8c2b2ce0e2de43eb96b294941a1d3315cd73d2563d77e246b286
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