Instructions to use mustapha/swin-tiny-patch4-window7-224-aiornot-simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mustapha/swin-tiny-patch4-window7-224-aiornot-simple with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mustapha/swin-tiny-patch4-window7-224-aiornot-simple") 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("mustapha/swin-tiny-patch4-window7-224-aiornot-simple") model = AutoModelForImageClassification.from_pretrained("mustapha/swin-tiny-patch4-window7-224-aiornot-simple", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec865737f50a24f13cae8fe5e24807fa35f3cd89d563417674a4874a4e4c21ec
- Size of remote file:
- 3.52 kB
- SHA256:
- 5eaf7e74786fde9d381960b4c32fb28ca6ccd060de037c69f4bebc51bcdb40d5
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