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README.md
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license: apache-2.0
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---
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# Model card for kat_tiny_patch16_224
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license: apache-2.0
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---
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# Model card for kat_tiny_patch16_224
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## Usage
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```python
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from urllib.request import urlopen
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from PIL import Image
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import timm
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import torch
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import katransformer
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img = Image.open(urlopen(
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'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
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))
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# Move model to CUDA
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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model = timm.create_model('hf_hub:adamdad/kat_tiny_patch16_224', pretrained=True)
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model = model.to(device)
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model = model.eval()
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# get model specific transforms (normalization, resize)
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data_config = timm.data.resolve_model_data_config(model)
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transforms = timm.data.create_transform(**data_config, is_training=False)
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output = model(transforms(img).unsqueeze(0).to(device)) # unsqueeze single image into batch of 1
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top5_probabilities, top5_class_indices = torch.topk(output.softmax(dim=1) * 100, k=5)
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print(top5_probabilities)
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print(top5_class_indices)
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```
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