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:
- 62eca87c7165260b72f9a0b907d2d5b86c58024743f5803c52f3d03e9928ed65
- Size of remote file:
- 372 MB
- SHA256:
- b86118c6986c719ae95bbf5d9cbd950449e9df2151658d4e5a4e10daaa6e2074
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