Image Classification
Transformers
Safetensors
English
siglip
Rice
Classification
SigLIP2
Type-Count:05
Instructions to use prithivMLmods/Rice-Leaf-Disease with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Rice-Leaf-Disease with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Rice-Leaf-Disease") 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/Rice-Leaf-Disease") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Rice-Leaf-Disease", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a9e6c82da78401b5c920abba9bf0dfa22c77ac7d9e99bc7830fa0ee898cc63a
- Size of remote file:
- 5.3 kB
- SHA256:
- 0a8827d78a733fd6830ab676c50e4c977f204759ddbc6e350b3f04d5c95fe641
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.