Instructions to use hf-tiny-model-private/tiny-random-SwinForImageClassification 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-SwinForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-tiny-model-private/tiny-random-SwinForImageClassification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-SwinForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-tiny-model-private/tiny-random-SwinForImageClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3aab00c068e3ce5a2d715601830a7aefcbef0f96be867fa903d8a3e3fb8a6863
- Size of remote file:
- 266 kB
- SHA256:
- 074ca734402d0e24818813661213ce625edf0357bd54d351b4ff5db47192b751
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