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* added chatGLM readme * changed wording in readme * added readme for chinese-clip * added readme for convmixer * added readme for custom ops * added readme for efficientnet * added readme for llama * added readme to mnist-training * added readme to musicgen * added readme to quantized-phi * added readme to starcoder2 * added readme to whisper-microphone * added readme to yi * added readme to yolo-v3 * added readme to whisper-microphone * added space to example in glm4 readme * fixed mamba example readme to run mamba instead of mamba-minimal * removed slash escape character * changed moondream image to yolo-v8 example image * added procedure for making the reinforcement-learning example work with a virtual environment on my machine * added simple one line summaries to the example readmes without * changed non-existant image to yolo example's bike.jpg * added backslash to sam command * removed trailing - from siglip * added SoX to silero-vad example readme * replaced procedure for uv on mac with warning that uv isn't currently compatible with pyo3 * added example to falcon readme * added --which arg to stella-en-v5 readme * fixed image path in vgg readme * fixed the image path in the vit readme * Update README.md * Update README.md * Update README.md --------- Co-authored-by: Laurent Mazare <laurent.mazare@gmail.com>
20 lines
611 B
Markdown
20 lines
611 B
Markdown
# 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 candle-examples/examples/yolo-v8/assets/bike.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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