Image Classification
Transformers
Safetensors
convnextv2
Generated from Trainer
Eval Results (legacy)
Instructions to use louislu9911/Expert1-leaf-disease-convnextv2-base-1k-224-0_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use louislu9911/Expert1-leaf-disease-convnextv2-base-1k-224-0_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="louislu9911/Expert1-leaf-disease-convnextv2-base-1k-224-0_4") 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("louislu9911/Expert1-leaf-disease-convnextv2-base-1k-224-0_4") model = AutoModelForImageClassification.from_pretrained("louislu9911/Expert1-leaf-disease-convnextv2-base-1k-224-0_4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 877 Bytes
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"_name_or_path": "facebook/convnextv2-base-1k-224",
"architectures": [
"ConvNextV2ForImageClassification"
],
"depths": [
3,
3,
27,
3
],
"drop_path_rate": 0.0,
"hidden_act": "gelu",
"hidden_sizes": [
128,
256,
512,
1024
],
"id2label": {
"0": 0,
"1": 1,
"2": 2,
"3": 3,
"4": 4
},
"image_size": 224,
"initializer_range": 0.02,
"label2id": {
"0": 0,
"1": 1,
"2": 2,
"3": 3,
"4": 4
},
"layer_norm_eps": 1e-12,
"model_type": "convnextv2",
"num_channels": 3,
"num_stages": 4,
"out_features": [
"stage4"
],
"out_indices": [
4
],
"patch_size": 4,
"problem_type": "single_label_classification",
"stage_names": [
"stem",
"stage1",
"stage2",
"stage3",
"stage4"
],
"torch_dtype": "float32",
"transformers_version": "4.39.3"
}
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