Instructions to use microsoft/swin-large-patch4-window12-384-in22k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/swin-large-patch4-window12-384-in22k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/swin-large-patch4-window12-384-in22k") 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("microsoft/swin-large-patch4-window12-384-in22k") model = AutoModelForImageClassification.from_pretrained("microsoft/swin-large-patch4-window12-384-in22k", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d5a544c181290abe3125d5dd06f6b59c1604c98f51e8f70529b15c81ca395ab
- Size of remote file:
- 919 MB
- SHA256:
- f2162687c1e8c50138c5c4cffe19ab0bdbe94497017a8c32945ce749fdd6831d
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