Instructions to use HorcruxNo13/swin-tiny-patch4-window7-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HorcruxNo13/swin-tiny-patch4-window7-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="HorcruxNo13/swin-tiny-patch4-window7-224") 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("HorcruxNo13/swin-tiny-patch4-window7-224") model = AutoModelForImageClassification.from_pretrained("HorcruxNo13/swin-tiny-patch4-window7-224") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c160e10fd2951d46611c1b02835f9715765be95f18bcc3ebe9919f121778d10
- Size of remote file:
- 110 MB
- SHA256:
- ffa7ac51ae0a31c1b522fc237eec55bf813983a9f7ef2df7521807481e6edc8b
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