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")# pip install -U transformers accelerate # 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") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from microsoft/swin-large-patch4-window12-384-in22k: direct link, hf CLI and curl.
- Browser
- Download file 916 MB
-
https://huggingface.co/microsoft/swin-large-patch4-window12-384-in22k/resolve/main/tf_model.h5
- Command line
-
hf download hf://microsoft/swin-large-patch4-window12-384-in22k/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/microsoft/swin-large-patch4-window12-384-in22k/resolve/main/tf_model.h5
916 MB
- Xet hash:
- 1a73dfb8c87eef6328c719b2f28a2a8eb77111bb4cd27fbebb5efc459984de76
- Size of remote file:
- 916 MB
- SHA256:
- 7c6595927220bd10715884b48424a0a40d6a301ce719d2c05f11a4c9e4dce719
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