Image Classification
Transformers
TensorBoard
Safetensors
swinv2
Generated from Trainer
Eval Results (legacy)
Instructions to use pk3388/swinv2-tiny-patch4-window8-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pk3388/swinv2-tiny-patch4-window8-256 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pk3388/swinv2-tiny-patch4-window8-256") 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("pk3388/swinv2-tiny-patch4-window8-256") model = AutoModelForImageClassification.from_pretrained("pk3388/swinv2-tiny-patch4-window8-256") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 41df7ffb51dc9b32fa1b5470d2e8e4755e0123d86265b024c6eeb4d4f6c908cb
- Size of remote file:
- 5.05 kB
- SHA256:
- 3a9b107ee04ecfeb4a796452fb9fd9ea71934b43746f08c8202a5b1f7d8db36e
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