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README.md
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@@ -35,32 +35,34 @@ 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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| SESR-M5-Quantized | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 1.
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| SESR-M5-Quantized | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 0.
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| SESR-M5-Quantized | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX |
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| SESR-M5-Quantized | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 1.
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| SESR-M5-Quantized | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 0.
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| SESR-M5-Quantized | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX |
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| SESR-M5-Quantized | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 1.
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| SESR-M5-Quantized | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 0.
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| SESR-M5-Quantized | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX |
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| SESR-M5-Quantized | RB3 Gen 2 (Proxy) | QCS6490 Proxy | TFLITE | 3.
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| SESR-M5-Quantized | RB3 Gen 2 (Proxy) | QCS6490 Proxy | QNN |
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| SESR-M5-Quantized | RB5 (Proxy) | QCS8250 Proxy | TFLITE | 21.
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| SESR-M5-Quantized | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 1.
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| SESR-M5-Quantized | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 0.
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@@ -126,7 +128,7 @@ SESR-M5-Quantized
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Device : Samsung Galaxy S23 (13)
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Runtime : TFLITE
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Estimated inference time (ms) : 1.4
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Estimated peak memory usage (MB): [0,
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Total # Ops : 27
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Compute Unit(s) : NPU (24 ops) CPU (3 ops)
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```
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import torch
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import qai_hub as hub
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from qai_hub_models.models.sesr_m5_quantized import
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# Load the model
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# Device
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device = hub.Device("Samsung Galaxy S23")
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```
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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-Quantized | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 1.356 ms | 0 - 7 MB | INT8 | NPU | [SESR-M5-Quantized.tflite](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.tflite) |
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| SESR-M5-Quantized | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 0.98 ms | 0 - 56 MB | INT8 | NPU | [SESR-M5-Quantized.so](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.so) |
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| SESR-M5-Quantized | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 2.724 ms | 0 - 3 MB | INT8 | NPU | [SESR-M5-Quantized.onnx](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.onnx) |
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| SESR-M5-Quantized | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 1.125 ms | 0 - 14 MB | INT8 | NPU | [SESR-M5-Quantized.tflite](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.tflite) |
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| SESR-M5-Quantized | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 0.712 ms | 0 - 14 MB | INT8 | NPU | [SESR-M5-Quantized.so](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.so) |
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| SESR-M5-Quantized | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 1.958 ms | 0 - 75 MB | INT8 | NPU | [SESR-M5-Quantized.onnx](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.onnx) |
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| SESR-M5-Quantized | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 1.025 ms | 0 - 11 MB | INT8 | NPU | [SESR-M5-Quantized.tflite](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.tflite) |
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| SESR-M5-Quantized | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 0.615 ms | 0 - 12 MB | INT8 | NPU | Use Export Script |
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| SESR-M5-Quantized | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 1.874 ms | 0 - 55 MB | INT8 | NPU | [SESR-M5-Quantized.onnx](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.onnx) |
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| SESR-M5-Quantized | RB3 Gen 2 (Proxy) | QCS6490 Proxy | TFLITE | 3.795 ms | 2 - 16 MB | INT8 | NPU | [SESR-M5-Quantized.tflite](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.tflite) |
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| SESR-M5-Quantized | RB3 Gen 2 (Proxy) | QCS6490 Proxy | QNN | 2.988 ms | 0 - 7 MB | INT8 | NPU | Use Export Script |
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| SESR-M5-Quantized | RB5 (Proxy) | QCS8250 Proxy | TFLITE | 21.37 ms | 2 - 11 MB | INT8 | NPU | [SESR-M5-Quantized.tflite](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.tflite) |
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| SESR-M5-Quantized | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 1.364 ms | 0 - 66 MB | INT8 | NPU | [SESR-M5-Quantized.tflite](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.tflite) |
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| SESR-M5-Quantized | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 0.697 ms | 0 - 1 MB | INT8 | NPU | Use Export Script |
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| SESR-M5-Quantized | SA7255P ADP | SA7255P | TFLITE | 14.621 ms | 2 - 13 MB | INT8 | NPU | [SESR-M5-Quantized.tflite](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.tflite) |
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| SESR-M5-Quantized | SA7255P ADP | SA7255P | QNN | 10.962 ms | 0 - 5 MB | INT8 | NPU | Use Export Script |
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| SESR-M5-Quantized | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 1.363 ms | 0 - 4 MB | INT8 | NPU | [SESR-M5-Quantized.tflite](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.tflite) |
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| SESR-M5-Quantized | SA8255 (Proxy) | SA8255P Proxy | QNN | 0.687 ms | 0 - 2 MB | INT8 | NPU | Use Export Script |
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| SESR-M5-Quantized | SA8295P ADP | SA8295P | TFLITE | 2.534 ms | 0 - 10 MB | INT8 | NPU | [SESR-M5-Quantized.tflite](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.tflite) |
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| SESR-M5-Quantized | SA8295P ADP | SA8295P | QNN | 2.132 ms | 0 - 6 MB | INT8 | NPU | Use Export Script |
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| SESR-M5-Quantized | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 1.353 ms | 0 - 17 MB | INT8 | NPU | [SESR-M5-Quantized.tflite](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.tflite) |
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| SESR-M5-Quantized | SA8650 (Proxy) | SA8650P Proxy | QNN | 0.687 ms | 0 - 1 MB | INT8 | NPU | Use Export Script |
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| SESR-M5-Quantized | SA8775P ADP | SA8775P | TFLITE | 2.438 ms | 0 - 10 MB | INT8 | NPU | [SESR-M5-Quantized.tflite](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.tflite) |
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| SESR-M5-Quantized | SA8775P ADP | SA8775P | QNN | 1.297 ms | 0 - 6 MB | INT8 | NPU | Use Export Script |
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| SESR-M5-Quantized | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 2.49 ms | 0 - 13 MB | INT8 | NPU | [SESR-M5-Quantized.tflite](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.tflite) |
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| SESR-M5-Quantized | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 1.124 ms | 0 - 15 MB | INT8 | NPU | Use Export Script |
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| SESR-M5-Quantized | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 1.226 ms | 0 - 0 MB | INT8 | NPU | Use Export Script |
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| SESR-M5-Quantized | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 3.152 ms | 2 - 2 MB | INT8 | NPU | [SESR-M5-Quantized.onnx](https://huggingface.co/qualcomm/SESR-M5-Quantized/blob/main/SESR-M5-Quantized.onnx) |
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Device : Samsung Galaxy S23 (13)
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Runtime : TFLITE
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Estimated inference time (ms) : 1.4
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Estimated peak memory usage (MB): [0, 7]
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Total # Ops : 27
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Compute Unit(s) : NPU (24 ops) CPU (3 ops)
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```
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import torch
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import qai_hub as hub
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from qai_hub_models.models.sesr_m5_quantized import Model
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# Load the 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()
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sample_inputs = torch_model.sample_inputs()
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pt_model = torch.jit.trace(torch_model, [torch.tensor(data[0]) for _, data in sample_inputs.items()])
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# Compile model on a specific device
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compile_job = hub.submit_compile_job(
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model=pt_model,
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device=device,
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input_specs=torch_model.get_input_spec(),
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)
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# Get target model to run on-device
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target_model = compile_job.get_target_model()
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```
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