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README.md
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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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| ResNeXt50 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 2.
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| ResNeXt50 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 2.
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| ResNeXt50 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 2.
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| ResNeXt50 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 1.
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| ResNeXt50 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 1.
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| ResNeXt50 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 2.
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| ResNeXt50 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 1.
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| ResNeXt50 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 1.
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| ResNeXt50 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 1.
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| ResNeXt50 | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 2.482 ms | 0 -
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| ResNeXt50 | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 2.
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| ResNeXt50 | SA7255P ADP | SA7255P | TFLITE | 85.
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| ResNeXt50 | SA7255P ADP | SA7255P | QNN | 85.
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| ResNeXt50 | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 2.
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| ResNeXt50 | SA8255 (Proxy) | SA8255P Proxy | QNN | 2.
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| ResNeXt50 | SA8295P ADP | SA8295P | TFLITE | 3.
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| ResNeXt50 | SA8295P ADP | SA8295P | QNN | 4.
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| ResNeXt50 | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 2.
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| ResNeXt50 | SA8650 (Proxy) | SA8650P Proxy | QNN | 2.
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| ResNeXt50 | SA8775P ADP | SA8775P | TFLITE | 4.
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| ResNeXt50 | SA8775P ADP | SA8775P | QNN | 4.
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| ResNeXt50 | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 3.246 ms | 0 - 27 MB | FP16 | NPU | [ResNeXt50.tflite](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.tflite) |
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| ResNeXt50 | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 3.
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| ResNeXt50 | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 2.
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| ResNeXt50 | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 2.
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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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Device : Samsung Galaxy S23 (13)
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Runtime : TFLITE
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Estimated inference time (ms) : 2.5
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Estimated peak memory usage (MB): [0,
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Total # Ops : 79
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Compute Unit(s) : NPU (79 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
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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 ResNeXt50 can be found
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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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| ResNeXt50 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 2.468 ms | 0 - 180 MB | FP16 | NPU | [ResNeXt50.tflite](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.tflite) |
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| ResNeXt50 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 2.543 ms | 1 - 131 MB | FP16 | NPU | [ResNeXt50.so](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.so) |
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| ResNeXt50 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 2.786 ms | 0 - 163 MB | FP16 | NPU | [ResNeXt50.onnx](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.onnx) |
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| ResNeXt50 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 1.756 ms | 0 - 38 MB | FP16 | NPU | [ResNeXt50.tflite](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.tflite) |
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| ResNeXt50 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 1.846 ms | 1 - 40 MB | FP16 | NPU | [ResNeXt50.so](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.so) |
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| ResNeXt50 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 2.107 ms | 0 - 40 MB | FP16 | NPU | [ResNeXt50.onnx](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.onnx) |
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| ResNeXt50 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 1.681 ms | 0 - 42 MB | FP16 | NPU | [ResNeXt50.tflite](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.tflite) |
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| ResNeXt50 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 1.511 ms | 1 - 41 MB | FP16 | NPU | Use Export Script |
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| ResNeXt50 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 1.99 ms | 1 - 43 MB | FP16 | NPU | [ResNeXt50.onnx](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.onnx) |
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| ResNeXt50 | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 2.482 ms | 0 - 191 MB | FP16 | NPU | [ResNeXt50.tflite](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.tflite) |
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| ResNeXt50 | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 2.522 ms | 1 - 3 MB | FP16 | NPU | Use Export Script |
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| ResNeXt50 | SA7255P ADP | SA7255P | TFLITE | 85.485 ms | 0 - 38 MB | FP16 | NPU | [ResNeXt50.tflite](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.tflite) |
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| ResNeXt50 | SA7255P ADP | SA7255P | QNN | 85.779 ms | 1 - 10 MB | FP16 | NPU | Use Export Script |
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| ResNeXt50 | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 2.473 ms | 0 - 191 MB | FP16 | NPU | [ResNeXt50.tflite](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.tflite) |
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| ResNeXt50 | SA8255 (Proxy) | SA8255P Proxy | QNN | 2.53 ms | 1 - 4 MB | FP16 | NPU | Use Export Script |
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| ResNeXt50 | SA8295P ADP | SA8295P | TFLITE | 3.969 ms | 0 - 27 MB | FP16 | NPU | [ResNeXt50.tflite](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.tflite) |
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| ResNeXt50 | SA8295P ADP | SA8295P | QNN | 4.305 ms | 0 - 14 MB | FP16 | NPU | Use Export Script |
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| ResNeXt50 | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 2.493 ms | 0 - 181 MB | FP16 | NPU | [ResNeXt50.tflite](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.tflite) |
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| ResNeXt50 | SA8650 (Proxy) | SA8650P Proxy | QNN | 2.51 ms | 1 - 3 MB | FP16 | NPU | Use Export Script |
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| ResNeXt50 | SA8775P ADP | SA8775P | TFLITE | 4.599 ms | 0 - 37 MB | FP16 | NPU | [ResNeXt50.tflite](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.tflite) |
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| ResNeXt50 | SA8775P ADP | SA8775P | QNN | 4.696 ms | 0 - 10 MB | FP16 | NPU | Use Export Script |
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| ResNeXt50 | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 3.246 ms | 0 - 27 MB | FP16 | NPU | [ResNeXt50.tflite](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.tflite) |
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| ResNeXt50 | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 3.363 ms | 1 - 28 MB | FP16 | NPU | Use Export Script |
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| ResNeXt50 | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 2.63 ms | 1 - 1 MB | FP16 | NPU | Use Export Script |
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| ResNeXt50 | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 2.642 ms | 52 - 52 MB | FP16 | NPU | [ResNeXt50.onnx](https://huggingface.co/qualcomm/ResNeXt50/blob/main/ResNeXt50.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
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```
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Device : Samsung Galaxy S23 (13)
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Runtime : TFLITE
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Estimated inference time (ms) : 2.5
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Estimated peak memory usage (MB): [0, 180]
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Total # Ops : 79
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Compute Unit(s) : NPU (79 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 ResNeXt50 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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