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@@ -35,8 +35,8 @@ More details on model performance across various devices, can be found
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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 | 3.349 ms | 0 - 2 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.tflite)
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- | Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 5.37 ms | 1 - 8 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.so](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.so)
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  ## Installation
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  This model can be installed as a Python package via pip.
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  ```bash
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- pip install qai-hub-models
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  ```
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  ## Configure Qualcomm® AI Hub to run this model on a cloud-hosted device
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  Sign-in to [Qualcomm® AI Hub](https://app.aihub.qualcomm.com/) with your
@@ -97,7 +98,7 @@ python -m qai_hub_models.models.deeplabv3_plus_mobilenet_quantized.export
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  Profile Job summary of DeepLabV3-Plus-MobileNet-Quantized
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  --------------------------------------------------
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  Device: Snapdragon X Elite CRD (11)
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- Estimated Inference Time: 5.34 ms
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  Estimated Peak Memory Range: 0.75-0.75 MB
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  Compute Units: NPU (100) | Total (100)
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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 | 3.331 ms | 0 - 3 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.tflite)
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+ | Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 5.345 ms | 0 - 45 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.so](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.so)
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  ## Installation
 
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  This model can be installed as a Python package via pip.
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  ```bash
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+ pip install "qai-hub-models[deeplabv3_plus_mobilenet_quantized]"
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  ```
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+
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  ## Configure Qualcomm® AI Hub to run this model on a cloud-hosted device
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  Sign-in to [Qualcomm® AI Hub](https://app.aihub.qualcomm.com/) with your
 
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  Profile Job summary of DeepLabV3-Plus-MobileNet-Quantized
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  --------------------------------------------------
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  Device: Snapdragon X Elite CRD (11)
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+ Estimated Inference Time: 5.38 ms
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  Estimated Peak Memory Range: 0.75-0.75 MB
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  Compute Units: NPU (100) | Total (100)
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