Image Classification
Transformers
TensorBoard
Safetensors
resnet
Generated from Trainer
Eval Results (legacy)
Instructions to use A2H0H0R1/resnet-50-plant-disease with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use A2H0H0R1/resnet-50-plant-disease with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="A2H0H0R1/resnet-50-plant-disease") 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("A2H0H0R1/resnet-50-plant-disease") model = AutoModelForImageClassification.from_pretrained("A2H0H0R1/resnet-50-plant-disease", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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tags:
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu121
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- Tokenizers 0.15.0
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tags:
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- generated_from_trainer
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datasets:
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metrics:
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- accuracy
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model-index:
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.16.0
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- Tokenizers 0.15.0
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