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Add a readme for the resnet example. (#1129)
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- DINOv2.
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- DINOv2.
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- ConvMixer.
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- ConvMixer.
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- EfficientNet.
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- EfficientNet.
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- ResNet-18/34.
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- yolo-v3.
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- yolo-v3.
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- yolo-v8.
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- yolo-v8.
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- Segment-Anything Model (SAM).
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- Segment-Anything Model (SAM).
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candle-examples/examples/resnet/README.md
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candle-examples/examples/resnet/README.md
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# candle-resnet
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A candle implementation of inference using a pre-trained [ResNet](https://arxiv.org/abs/1512.03385).
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This uses a classification head trained on the ImageNet dataset and returns the
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probabilities for the top-5 classes.
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## Running an example
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```
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$ cargo run --example resnet --release -- --image tiger.jpg
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loaded image Tensor[dims 3, 224, 224; f32]
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model built
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tiger, Panthera tigris : 90.21%
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tiger cat : 8.93%
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lion, king of beasts, Panthera leo: 0.35%
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leopard, Panthera pardus: 0.16%
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jaguar, panther, Panthera onca, Felis onca: 0.09%
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```
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