Instructions to use OttoYu/Tree-Condition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OttoYu/Tree-Condition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="OttoYu/Tree-Condition") 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("OttoYu/Tree-Condition") model = AutoModelForImageClassification.from_pretrained("OttoYu/Tree-Condition") - Notebooks
- Google Colab
- Kaggle
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README.md
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example_title: Bacterial canker
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- src: https://bit.ly/3LYSGn6
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example_title: Citrus canker
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co2_eq_emissions:
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emissions: 1.3038362907488008
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example_title: Bacterial canker
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- src: https://bit.ly/3LYSGn6
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example_title: Citrus canker
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- src: https://www.elitetreecare.com/wp-content/uploads/2016/06/black-knot.jpg
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example_title: Black knot
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- src: https://gtr-arbor.com.hk/wp-content/uploads/2015/01/fungi2-5.jpg
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example_title: Fungi
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- src: https://gtr-arbor.com.hk/wp-content/uploads/2011/05/insectA2-2.jpg
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example_title: Termite
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co2_eq_emissions:
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emissions: 1.3038362907488008
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