Image Classification
Transformers
TensorBoard
Safetensors
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use Sara5115/swin-tiny-patch4-window7-224-BlurClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sara5115/swin-tiny-patch4-window7-224-BlurClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sara5115/swin-tiny-patch4-window7-224-BlurClassification") 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("Sara5115/swin-tiny-patch4-window7-224-BlurClassification") model = AutoModelForImageClassification.from_pretrained("Sara5115/swin-tiny-patch4-window7-224-BlurClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-3/optimizer.pt from Sara5115/swin-tiny-patch4-window7-224-BlurClassification: direct link, hf CLI and curl.
- Browser
- Download file 220 MB
-
https://huggingface.co/Sara5115/swin-tiny-patch4-window7-224-BlurClassification/resolve/main/checkpoint-3/optimizer.pt
- Command line
-
hf download hf://Sara5115/swin-tiny-patch4-window7-224-BlurClassification/checkpoint-3/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Sara5115/swin-tiny-patch4-window7-224-BlurClassification/resolve/main/checkpoint-3/optimizer.pt
220 MB
- Xet hash:
- b28ba4e3590b862d9dd8cc1c9b4955bcb2507e967068ecebd23122cd7ed08d72
- Size of remote file:
- 220 MB
- SHA256:
- 6da7fde72668dc43557b236b5974cfd1229df9410e58f3156ad99018993cf6cb
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