Instructions to use hf-tiny-model-private/tiny-random-DinatBackbone 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-DinatBackbone with Transformers:
# Load model directly from transformers import AutoImageProcessor, DinatBackbone processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-DinatBackbone") model = DinatBackbone.from_pretrained("hf-tiny-model-private/tiny-random-DinatBackbone", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 052670aa944f714ae50c32e2a562ff61b34fab6f6e03b654c4ec9fd64e5dcf07
- Size of remote file:
- 339 kB
- SHA256:
- caa2cbbf9c8a5fa4ca810e2fe858d312ca1be4c51ce3d054b30b6a1ae1c162c2
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