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Upload README.md with huggingface_hub

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@@ -30,14 +30,15 @@ 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: 27.5M
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  - Model size: 105 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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  | ---|---|---|---|---|---|---|---|
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- | Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 23.277 ms | 0 - 2 MB | FP16 | NPU | [FFNet-78S.tflite](https://huggingface.co/qualcomm/FFNet-78S/blob/main/FFNet-78S.tflite)
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- | Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 24.928 ms | 24 - 45 MB | FP16 | NPU | [FFNet-78S.so](https://huggingface.co/qualcomm/FFNet-78S/blob/main/FFNet-78S.so)
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@@ -100,8 +101,8 @@ python -m qai_hub_models.models.ffnet_78s.export
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  Profile Job summary of FFNet-78S
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  --------------------------------------------------
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  Device: SA8255 (Proxy) (13)
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- Estimated Inference Time: 23.86 ms
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- Estimated Peak Memory Range: 24.07-45.49 MB
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  Compute Units: NPU (235) | Total (235)
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  - Input resolution: 2048x1024
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  - Number of parameters: 27.5M
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  - Model size: 105 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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  | ---|---|---|---|---|---|---|---|
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+ | Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 23.829 ms | 2 - 5 MB | FP16 | NPU | [FFNet-78S.tflite](https://huggingface.co/qualcomm/FFNet-78S/blob/main/FFNet-78S.tflite)
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+ | Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 23.711 ms | 26 - 46 MB | FP16 | NPU | [FFNet-78S.so](https://huggingface.co/qualcomm/FFNet-78S/blob/main/FFNet-78S.so)
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  Profile Job summary of FFNet-78S
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  --------------------------------------------------
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  Device: SA8255 (Proxy) (13)
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+ Estimated Inference Time: 23.75 ms
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+ Estimated Peak Memory Range: 23.07-40.26 MB
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  Compute Units: NPU (235) | Total (235)
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