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:
- ec9c85cde3ca74097e9ed21c89b6eb1b0bd087b1b6a897d58771b65f790b0faf
- Size of remote file:
- 378 kB
- SHA256:
- f89a07fe10fdcd78e6aaecdbc23e61b6aff5527d9478766796e8e3ff6de74250
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