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@@ -35,34 +35,33 @@ More details on model performance across various devices, can be found
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  | Model | 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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- | ResNet-Mixed-Convolution | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 167.191 ms | 30 - 76 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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- | ResNet-Mixed-Convolution | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 17.682 ms | 0 - 91 MB | FP16 | NPU | [ResNet-Mixed-Convolution.onnx](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.onnx) |
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- | ResNet-Mixed-Convolution | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 127.47 ms | 29 - 58 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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- | ResNet-Mixed-Convolution | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 13.111 ms | 4 - 70 MB | FP16 | NPU | [ResNet-Mixed-Convolution.onnx](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.onnx) |
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- | ResNet-Mixed-Convolution | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 150.781 ms | 29 - 59 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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- | ResNet-Mixed-Convolution | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 12.757 ms | 2 - 64 MB | FP16 | NPU | [ResNet-Mixed-Convolution.onnx](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.onnx) |
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- | ResNet-Mixed-Convolution | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 166.676 ms | 31 - 57 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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- | ResNet-Mixed-Convolution | SA7255P ADP | SA7255P | TFLITE | 1030.441 ms | 31 - 57 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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- | ResNet-Mixed-Convolution | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 166.883 ms | 31 - 82 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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- | ResNet-Mixed-Convolution | SA8295P ADP | SA8295P | TFLITE | 203.1 ms | 31 - 59 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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- | ResNet-Mixed-Convolution | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 169.72 ms | 30 - 75 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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- | ResNet-Mixed-Convolution | SA8775P ADP | SA8775P | TFLITE | 219.728 ms | 31 - 58 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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- | ResNet-Mixed-Convolution | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 184.655 ms | 31 - 60 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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- | ResNet-Mixed-Convolution | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 18.869 ms | 25 - 25 MB | FP16 | NPU | [ResNet-Mixed-Convolution.onnx](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.onnx) |
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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[resnet_mixed]"
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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
@@ -113,8 +112,8 @@ Profiling Results
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  ResNet-Mixed-Convolution
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  Device : Samsung Galaxy S23 (13)
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  Runtime : TFLITE
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- Estimated inference time (ms) : 167.2
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- Estimated peak memory usage (MB): [30, 76]
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  Total # Ops : 55
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  Compute Unit(s) : NPU (50 ops) CPU (5 ops)
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  ```
@@ -141,7 +140,7 @@ from qai_hub_models.models.resnet_mixed import Model
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  torch_model = Model.from_pretrained()
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  # Device
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- device = hub.Device("Samsung Galaxy S23")
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  # Trace model
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  input_shape = torch_model.get_input_spec()
@@ -219,7 +218,8 @@ Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)
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  ## License
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- * The license for the original implementation of ResNet-Mixed-Convolution can be found [here](https://github.com/pytorch/vision/blob/main/LICENSE).
 
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  * The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf)
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  | Model | 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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+ | ResNet-Mixed-Convolution | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 165.098 ms | 31 - 76 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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+ | ResNet-Mixed-Convolution | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 17.778 ms | 2 - 73 MB | FP16 | NPU | [ResNet-Mixed-Convolution.onnx](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.onnx) |
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+ | ResNet-Mixed-Convolution | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 125.942 ms | 30 - 59 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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+ | ResNet-Mixed-Convolution | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 13.274 ms | 4 - 68 MB | FP16 | NPU | [ResNet-Mixed-Convolution.onnx](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.onnx) |
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+ | ResNet-Mixed-Convolution | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 151.691 ms | 30 - 61 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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+ | ResNet-Mixed-Convolution | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 12.489 ms | 3 - 67 MB | FP16 | NPU | [ResNet-Mixed-Convolution.onnx](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.onnx) |
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+ | ResNet-Mixed-Convolution | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 166.515 ms | 31 - 86 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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+ | ResNet-Mixed-Convolution | SA7255P ADP | SA7255P | TFLITE | 1030.612 ms | 31 - 58 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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+ | ResNet-Mixed-Convolution | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 165.831 ms | 31 - 46 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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+ | ResNet-Mixed-Convolution | SA8295P ADP | SA8295P | TFLITE | 201.377 ms | 31 - 59 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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+ | ResNet-Mixed-Convolution | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 164.869 ms | 31 - 56 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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+ | ResNet-Mixed-Convolution | SA8775P ADP | SA8775P | TFLITE | 219.65 ms | 31 - 58 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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+ | ResNet-Mixed-Convolution | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 193.127 ms | 31 - 60 MB | FP16 | NPU | [ResNet-Mixed-Convolution.tflite](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.tflite) |
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+ | ResNet-Mixed-Convolution | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 18.965 ms | 24 - 24 MB | FP16 | NPU | [ResNet-Mixed-Convolution.onnx](https://huggingface.co/qualcomm/ResNet-Mixed-Convolution/blob/main/ResNet-Mixed-Convolution.onnx) |
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  ## Installation
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+ Install the package via pip:
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  ```bash
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+ pip install "qai-hub-models[resnet-mixed]"
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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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  ResNet-Mixed-Convolution
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  Device : Samsung Galaxy S23 (13)
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  Runtime : TFLITE
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+ Estimated inference time (ms) : 165.1
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+ Estimated peak memory usage (MB): [31, 76]
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  Total # Ops : 55
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  Compute Unit(s) : NPU (50 ops) CPU (5 ops)
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  ```
 
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  torch_model = Model.from_pretrained()
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  # Device
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+ device = hub.Device("Samsung Galaxy S24")
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  # Trace model
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  input_shape = torch_model.get_input_spec()
 
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  ## License
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+ * The license for the original implementation of ResNet-Mixed-Convolution can be found
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+ [here](https://github.com/pytorch/vision/blob/main/LICENSE).
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  * The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf)
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