Instructions to use hf-tiny-model-private/tiny-random-SwinModel 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-SwinModel 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-SwinModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-SwinModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-SwinModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ffa648f51c21dc819b4d718bc4330b1a3ef24a9aa9ef36884f4aebe6613d22d4
- Size of remote file:
- 265 kB
- SHA256:
- 6c3cb48d38d2c3095f3772f98cabe00304a8b210b335efd5bfaf2dce581f2580
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