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README.md
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@@ -31,14 +31,15 @@ More details on model performance across various devices, can be found
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- Input resolution: 2048x1024
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- Number of parameters: 13.9M
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- Model size: 53.1 MB
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| Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
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| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 16.
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| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 17.
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Profile Job summary of FFNet-40S
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Device: SA8255 (Proxy) (13)
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Estimated Inference Time: 17.
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Estimated Peak Memory Range: 24.
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Compute Units: NPU (140) | Total (140)
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- Input resolution: 2048x1024
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- Number of parameters: 13.9M
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- Model size: 53.1 MB
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- Number of output classes: 19
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| Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
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| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 16.917 ms | 2 - 5 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite)
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| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 17.383 ms | 26 - 40 MB | FP16 | NPU | [FFNet-40S.so](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.so)
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Profile Job summary of FFNet-40S
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--------------------------------------------------
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Device: SA8255 (Proxy) (13)
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Estimated Inference Time: 17.20 ms
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Estimated Peak Memory Range: 24.04-37.86 MB
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Compute Units: NPU (140) | Total (140)
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