Instructions to use mruby/swin-tiny-patch4-window7-224-attempt-m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mruby/swin-tiny-patch4-window7-224-attempt-m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mruby/swin-tiny-patch4-window7-224-attempt-m") 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("mruby/swin-tiny-patch4-window7-224-attempt-m") model = AutoModelForImageClassification.from_pretrained("mruby/swin-tiny-patch4-window7-224-attempt-m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd8cdacc8b3e4870277726c8130747747c36eae6aee2071a2ac1a03625b57805
- Size of remote file:
- 110 MB
- SHA256:
- a8fec51951f74955d6c8038000ad12ad3c3f53e06bc55af8abcee019a8b7fe73
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