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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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| SESR-M5 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 2.
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| SESR-M5 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 2.
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| SESR-M5 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 2.
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| SESR-M5 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 1.
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| SESR-M5 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 1.
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| SESR-M5 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 1.
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| SESR-M5 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 1.
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| SESR-M5 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 1.
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| SESR-M5 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX |
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| SESR-M5 | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 2.
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| SESR-M5 | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 2.
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| SESR-M5 | SA7255P ADP | SA7255P | TFLITE |
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| SESR-M5 | SA7255P ADP | SA7255P | QNN | 77.
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| SESR-M5 | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 2.
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| SESR-M5 | SA8255 (Proxy) | SA8255P Proxy | QNN | 2.
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| SESR-M5 | SA8295P ADP | SA8295P | TFLITE |
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| SESR-M5 | SA8295P ADP | SA8295P | QNN |
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| SESR-M5 | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 2.
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| SESR-M5 | SA8650 (Proxy) | SA8650P Proxy | QNN | 2.
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| SESR-M5 | SA8775P ADP | SA8775P | TFLITE | 4.
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| SESR-M5 | SA8775P ADP | SA8775P | QNN | 4.
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| SESR-M5 | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 3.
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| SESR-M5 | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 3.
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| SESR-M5 | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 2.
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| SESR-M5 | 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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SESR-M5
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Device : Samsung Galaxy S23 (13)
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Runtime : TFLITE
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Estimated inference time (ms) : 2.
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Estimated peak memory usage (MB): [0,
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Total # Ops : 25
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Compute Unit(s) : NPU (22 ops) CPU (3 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 SESR-M5 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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| SESR-M5 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 2.242 ms | 0 - 5 MB | FP16 | NPU | [SESR-M5.tflite](https://huggingface.co/qualcomm/SESR-M5/blob/main/SESR-M5.tflite) |
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| SESR-M5 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 2.123 ms | 0 - 5 MB | FP16 | NPU | [SESR-M5.so](https://huggingface.co/qualcomm/SESR-M5/blob/main/SESR-M5.so) |
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| SESR-M5 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 2.727 ms | 0 - 6 MB | FP16 | NPU | [SESR-M5.onnx](https://huggingface.co/qualcomm/SESR-M5/blob/main/SESR-M5.onnx) |
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| SESR-M5 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 1.524 ms | 0 - 21 MB | FP16 | NPU | [SESR-M5.tflite](https://huggingface.co/qualcomm/SESR-M5/blob/main/SESR-M5.tflite) |
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| SESR-M5 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 1.468 ms | 0 - 28 MB | FP16 | NPU | [SESR-M5.so](https://huggingface.co/qualcomm/SESR-M5/blob/main/SESR-M5.so) |
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| SESR-M5 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 1.984 ms | 0 - 28 MB | FP16 | NPU | [SESR-M5.onnx](https://huggingface.co/qualcomm/SESR-M5/blob/main/SESR-M5.onnx) |
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| SESR-M5 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 1.848 ms | 0 - 17 MB | FP16 | NPU | [SESR-M5.tflite](https://huggingface.co/qualcomm/SESR-M5/blob/main/SESR-M5.tflite) |
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| SESR-M5 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 1.252 ms | 0 - 17 MB | FP16 | NPU | Use Export Script |
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| SESR-M5 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 1.665 ms | 0 - 17 MB | FP16 | NPU | [SESR-M5.onnx](https://huggingface.co/qualcomm/SESR-M5/blob/main/SESR-M5.onnx) |
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| SESR-M5 | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 2.198 ms | 0 - 6 MB | FP16 | NPU | [SESR-M5.tflite](https://huggingface.co/qualcomm/SESR-M5/blob/main/SESR-M5.tflite) |
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| SESR-M5 | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 2.162 ms | 0 - 4 MB | FP16 | NPU | Use Export Script |
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| SESR-M5 | SA7255P ADP | SA7255P | TFLITE | 79.929 ms | 6 - 16 MB | FP16 | NPU | [SESR-M5.tflite](https://huggingface.co/qualcomm/SESR-M5/blob/main/SESR-M5.tflite) |
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| SESR-M5 | SA7255P ADP | SA7255P | QNN | 77.375 ms | 0 - 10 MB | FP16 | NPU | Use Export Script |
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| SESR-M5 | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 2.271 ms | 0 - 5 MB | FP16 | NPU | [SESR-M5.tflite](https://huggingface.co/qualcomm/SESR-M5/blob/main/SESR-M5.tflite) |
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| SESR-M5 | SA8255 (Proxy) | SA8255P Proxy | QNN | 2.182 ms | 0 - 3 MB | FP16 | NPU | Use Export Script |
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| SESR-M5 | SA8295P ADP | SA8295P | TFLITE | 4.309 ms | 6 - 22 MB | FP16 | NPU | [SESR-M5.tflite](https://huggingface.co/qualcomm/SESR-M5/blob/main/SESR-M5.tflite) |
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| SESR-M5 | SA8295P ADP | SA8295P | QNN | 3.674 ms | 0 - 14 MB | FP16 | NPU | Use Export Script |
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| SESR-M5 | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 2.295 ms | 0 - 6 MB | FP16 | NPU | [SESR-M5.tflite](https://huggingface.co/qualcomm/SESR-M5/blob/main/SESR-M5.tflite) |
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| SESR-M5 | SA8650 (Proxy) | SA8650P Proxy | QNN | 2.169 ms | 0 - 3 MB | FP16 | NPU | Use Export Script |
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| SESR-M5 | SA8775P ADP | SA8775P | TFLITE | 4.5 ms | 6 - 17 MB | FP16 | NPU | [SESR-M5.tflite](https://huggingface.co/qualcomm/SESR-M5/blob/main/SESR-M5.tflite) |
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| SESR-M5 | SA8775P ADP | SA8775P | QNN | 4.479 ms | 0 - 10 MB | FP16 | NPU | Use Export Script |
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| SESR-M5 | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 3.751 ms | 6 - 29 MB | FP16 | NPU | [SESR-M5.tflite](https://huggingface.co/qualcomm/SESR-M5/blob/main/SESR-M5.tflite) |
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| SESR-M5 | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 3.294 ms | 0 - 19 MB | FP16 | NPU | Use Export Script |
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| SESR-M5 | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 2.349 ms | 0 - 0 MB | FP16 | NPU | Use Export Script |
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| SESR-M5 | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 2.989 ms | 9 - 9 MB | FP16 | NPU | [SESR-M5.onnx](https://huggingface.co/qualcomm/SESR-M5/blob/main/SESR-M5.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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SESR-M5
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Device : Samsung Galaxy S23 (13)
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Runtime : TFLITE
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Estimated inference time (ms) : 2.2
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Estimated peak memory usage (MB): [0, 5]
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Total # Ops : 25
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Compute Unit(s) : NPU (22 ops) CPU (3 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 SESR-M5 can be found
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[here](https://github.com/quic/aimet-model-zoo/blob/develop/LICENSE.pdf).
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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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