Image Classification
Transformers
Safetensors
English
siglip
SigLIP2
Flood-Detection
Disaster-Detection
climate
Instructions to use prithivMLmods/Flood-Image-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Flood-Image-Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Flood-Image-Detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Flood-Image-Detection") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Flood-Image-Detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-60/optimizer.pt from prithivMLmods/Flood-Image-Detection: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/prithivMLmods/Flood-Image-Detection/resolve/main/checkpoint-60/optimizer.pt
- Command line
-
hf download hf://prithivMLmods/Flood-Image-Detection/checkpoint-60/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/prithivMLmods/Flood-Image-Detection/resolve/main/checkpoint-60/optimizer.pt
687 MB
- Xet hash:
- d29db376462843c8208cb8f277496f0ae0475c4ad40754a274d25ea6fd3434d8
- Size of remote file:
- 687 MB
- SHA256:
- ad0bb40cce917c669d9c8513adc0094d738a91a1fa691c99c49818773cf90517
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