Image Classification
Transformers
Safetensors
English
siglip
Structures
Desert
Glacier
Street
Ocean
Image-Classifier
art
Mountain
Instructions to use prithivMLmods/Multilabel-GeoSceneNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Multilabel-GeoSceneNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Multilabel-GeoSceneNet") 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/Multilabel-GeoSceneNet") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Multilabel-GeoSceneNet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ea590f7470cf599b92aa5e69811ca8fadaeea3fe8d019bfab52d13db45d0183
- Size of remote file:
- 687 MB
- SHA256:
- 502bd51467ab759224edcdb26b212d22b5e39f96c49599a7e2d462765e9b2280
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