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:
- 0a2c59270de24ca70cb3beb3097a58a2a36f1cd34c6e076f77623722ddfc3337
- Size of remote file:
- 283 kB
- SHA256:
- d2a09f495ef0b830b5553a37337c69f0b224fad50d8eeb8cb8881c1fc5913f07
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