Image Classification
Transformers
Safetensors
English
siglip
Gaofen-Image-Dataset
Land-Cover-Classification
Remote-Sensing-Images
Instructions to use prithivMLmods/GiD-Land-Cover-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/GiD-Land-Cover-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/GiD-Land-Cover-Classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/GiD-Land-Cover-Classification") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/GiD-Land-Cover-Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47910dadf26d7c8b5b5c52e0bd35ed15fa57374409e64dba0946c81dcc225bac
- Size of remote file:
- 687 MB
- SHA256:
- c7069d03491ff6b7becd40226ae7ecf3cf4daf5e0bd21c455bcecf8a3a60bae7
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