Instructions to use firedfrog/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 firedfrog/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="firedfrog/swin-tiny-patch4-window7-224-finetuned-eurosat") 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("firedfrog/swin-tiny-patch4-window7-224-finetuned-eurosat") model = AutoModelForImageClassification.from_pretrained("firedfrog/swin-tiny-patch4-window7-224-finetuned-eurosat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from firedfrog/swin-tiny-patch4-window7-224-finetuned-eurosat: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/firedfrog/swin-tiny-patch4-window7-224-finetuned-eurosat/resolve/f859f6e55a4768616b899343ad9a1293134dbc0b/training_args.bin
- Command line
-
hf download hf://firedfrog/swin-tiny-patch4-window7-224-finetuned-eurosat@f859f6e55a4768616b899343ad9a1293134dbc0b/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/firedfrog/swin-tiny-patch4-window7-224-finetuned-eurosat/resolve/f859f6e55a4768616b899343ad9a1293134dbc0b/training_args.bin
5.18 kB
- Xet hash:
- 10e08a58266bdfa7aaae00193dfa1703a5e21d8a6bf8d3567cd47845dc69966f
- Size of remote file:
- 5.18 kB
- SHA256:
- 3678de274333f4a158a8e562a3ba491082d35a48149fa056dd89cc59c8d6da36
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