Image Classification
Transformers
PyTorch
TensorBoard
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use sasha/swin-tiny-finetuned-dogfood with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sasha/swin-tiny-finetuned-dogfood with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sasha/swin-tiny-finetuned-dogfood") 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("sasha/swin-tiny-finetuned-dogfood") model = AutoModelForImageClassification.from_pretrained("sasha/swin-tiny-finetuned-dogfood", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 851968d50a8c9188470a3d55b4304ad36cf77f9500bcee9c0570aad90a118833
- Size of remote file:
- 3.31 kB
- SHA256:
- 63200a377a019b8e64ec502d589cf1706f99a24dc4fa6d905516ba0a049c4673
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