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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 26c6f20bf96757d1599d1ad68d6a14b2d5c2e83b04637217d2135056b10aa804
- Size of remote file:
- 123 MB
- SHA256:
- 47a093be6ecea95376cafd6641ae3dad3064d3ad34107683439c5c2bb9b8e255
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