Instructions to use hf-tiny-model-private/tiny-random-DeformableDetrModel 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-DeformableDetrModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-tiny-model-private/tiny-random-DeformableDetrModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-DeformableDetrModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-DeformableDetrModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b47749c54dbba84e388338d43f808f17837f4abccba8a3a2bd08ab2dbac12e4
- Size of remote file:
- 123 MB
- SHA256:
- 48645b9f71849728fd7fbaed7e7dd4a411d6db23a5085f8924c70f10eddffa1d
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