Instructions to use hf-tiny-model-private/tiny-random-DetrForObjectDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-DetrForObjectDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="hf-tiny-model-private/tiny-random-DetrForObjectDetection")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-DetrForObjectDetection") model = AutoModelForObjectDetection.from_pretrained("hf-tiny-model-private/tiny-random-DetrForObjectDetection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 651150408f82553d195cc58a2577d8da5673f37936cbf496acf68bf5b956f4f2
- Size of remote file:
- 103 MB
- SHA256:
- 74201ef164a95db786c5fc1f6905d5d97d03591b0ad58b90a957ca6b031b16f7
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