Instructions to use Luna-Skywalker/corn_dtect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastai
How to use Luna-Skywalker/corn_dtect with fastai:
from huggingface_hub import from_pretrained_fastai learn = from_pretrained_fastai("Luna-Skywalker/corn_dtect") - timm
How to use Luna-Skywalker/corn_dtect with timm:
import timm model = timm.create_model("hf-hub:Luna-Skywalker/corn_dtect", pretrained=True) - Notebooks
- Google Colab
- Kaggle
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Download README.md from Luna-Skywalker/corn_dtect: direct link, hf CLI and curl.
- Browser
- Download file 693 Bytes
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https://huggingface.co/Luna-Skywalker/corn_dtect/resolve/main/README.md
- Command line
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hf download hf://Luna-Skywalker/corn_dtect/README.md
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curl -L -o README.md https://huggingface.co/Luna-Skywalker/corn_dtect/resolve/main/README.md
693 Bytes
| tags: | |
| - fastai | |
| - pytorch | |
| - timm | |
| license: mit | |
| metrics: | |
| - accuracy | |
| library_name: fastai | |
| pipeline_tag: image-classification | |
| # Potato disease detection | |
| This model is trained for detecting if the corn plant is healthy or if it has diseases like Common Rust, Gray Leaf Spot or Northern Leaf Blight | |
| # Enjoyy | |
| --- | |
| # Model card | |
| A ConvNeXT model used for image classfication. | |
| ## Model Details | |
| - **Model Type:** Image classification | |
| - **Papers:** | |
| - A ConvNet for the 2020s: https://arxiv.org/abs/2201.03545 | |
| - **Dataset:** New Bangladeshi Crop Disease: https://www.kaggle.com/datasets/nafishamoin/new-bangladeshi-crop-disease | |
| - **Original:** https://github.com/facebookresearch/ConvNeXt | |