Instructions to use bryanzhou008/swin-tiny-patch4-window7-224-finetuned-eurosat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bryanzhou008/swin-tiny-patch4-window7-224-finetuned-eurosat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bryanzhou008/swin-tiny-patch4-window7-224-finetuned-eurosat") 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("bryanzhou008/swin-tiny-patch4-window7-224-finetuned-eurosat") model = AutoModelForImageClassification.from_pretrained("bryanzhou008/swin-tiny-patch4-window7-224-finetuned-eurosat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 2.4, | |
| "eval_accuracy": 0.17777777777777778, | |
| "eval_loss": 2.99086856842041, | |
| "eval_runtime": 3.4315, | |
| "eval_samples_per_second": 209.819, | |
| "eval_steps_per_second": 1.748 | |
| } |