Image Classification
Transformers
PyTorch
TensorBoard
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use mshuggingface/swin-tiny-patch4-window7-224-ms-test1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mshuggingface/swin-tiny-patch4-window7-224-ms-test1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mshuggingface/swin-tiny-patch4-window7-224-ms-test1") 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("mshuggingface/swin-tiny-patch4-window7-224-ms-test1") model = AutoModelForImageClassification.from_pretrained("mshuggingface/swin-tiny-patch4-window7-224-ms-test1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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