Instructions to use AZIIIIIIIIZ/vit-base-patch16-224-finetuned-eurosat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AZIIIIIIIIZ/vit-base-patch16-224-finetuned-eurosat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="AZIIIIIIIIZ/vit-base-patch16-224-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("AZIIIIIIIIZ/vit-base-patch16-224-finetuned-eurosat") model = AutoModelForImageClassification.from_pretrained("AZIIIIIIIIZ/vit-base-patch16-224-finetuned-eurosat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AZIIIIIIIIZ/vit-base-patch16-224-finetuned-eurosat: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/AZIIIIIIIIZ/vit-base-patch16-224-finetuned-eurosat/resolve/main/training_args.bin
- Command line
-
hf download hf://AZIIIIIIIIZ/vit-base-patch16-224-finetuned-eurosat/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AZIIIIIIIIZ/vit-base-patch16-224-finetuned-eurosat/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- d5199f16415f7c489667563560e2837939904ba33be7cbfe8615eb7cd25dc2d2
- Size of remote file:
- 5.18 kB
- SHA256:
- 5428b3e3c402213df9ea4e225ac99709961adbb1160b940f1c736c2ff122b956
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