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:
- 1ca22ab78753cac5bbd510949e1222421276f30e6d94c2882a222557860dd651
- Size of remote file:
- 372 MB
- SHA256:
- 433992cdfa082e2ee54f3c418dcd7efde631d6cf4664d36e234bb1c431cc49f4
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