Instructions to use hf-tiny-model-private/tiny-random-DeformableDetrForObjectDetection 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-DeformableDetrForObjectDetection 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-DeformableDetrForObjectDetection")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-DeformableDetrForObjectDetection") model = AutoModelForObjectDetection.from_pretrained("hf-tiny-model-private/tiny-random-DeformableDetrForObjectDetection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9b6702f24d50305ec3322c475416219c05cb29c7b15d285f4c75c099964bb36
- Size of remote file:
- 123 MB
- SHA256:
- 4a6a37b1184e40ade6a6363387c8ccc7ccb38903e547d46094563e94bdfa8178
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