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:
- 6abf48f15251159c5b0426982fe33a3d8d8d8be5b87da20bf63c26ea3f471fe1
- Size of remote file:
- 285 kB
- SHA256:
- 6e73c9bd31918450ca30bac9f5fd56c615038b393afd8d1eed487778d832e19d
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