Instructions to use HorcruxNo13/swin-tiny-patch4-window7-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HorcruxNo13/swin-tiny-patch4-window7-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="HorcruxNo13/swin-tiny-patch4-window7-224") 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("HorcruxNo13/swin-tiny-patch4-window7-224") model = AutoModelForImageClassification.from_pretrained("HorcruxNo13/swin-tiny-patch4-window7-224") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 7.0, | |
| "total_flos": 1.73991922900992e+17, | |
| "train_loss": 0.5527358267988477, | |
| "train_runtime": 138.7489, | |
| "train_samples_per_second": 50.451, | |
| "train_steps_per_second": 0.404 | |
| } |