Instructions to use haiderAI/vision-model-Vit-rice-leaf-disease-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use haiderAI/vision-model-Vit-rice-leaf-disease-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="haiderAI/vision-model-Vit-rice-leaf-disease-detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("haiderAI/vision-model-Vit-rice-leaf-disease-detection") model = AutoModelForImageClassification.from_pretrained("haiderAI/vision-model-Vit-rice-leaf-disease-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 499da5d8d7ef6df6773c57150be0a7483cef631352b7493d81963b5d6ffd1c24
- Size of remote file:
- 343 MB
- SHA256:
- d7aa68de7e8d535be206375b410fa97825e94597ba9d2195b5803de8c93bef28
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