v0.58.0
Browse filesSee https://github.com/qualcomm/ai-hub-models/releases/v0.58.0 for changelog.
- README.md +86 -80
- release_assets.json +6 -6
README.md
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@@ -16,7 +16,7 @@ pipeline_tag: image-classification
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EfficientNetV2-s is a machine learning model that can classify images from the Imagenet dataset. It can also be used as a backbone in building more complex models for specific use cases.
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This is based on the implementation of EfficientNet-V2-s found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/efficientnet.py).
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This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.
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Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.
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| Runtime | Precision | Chipset | SDK Versions | Download |
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|---|---|---|---|---|
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| ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.25.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.
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| ONNX | w8a16 | Universal | QAIRT 2.45, ONNX Runtime 1.25.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.
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| QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.
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| QNN_DLC | w8a16 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.
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| TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.
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For more device-specific assets and performance metrics, visit **[EfficientNet-V2-s on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/efficientnet_v2_s)**.
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### Option 2: Export with Custom Configurations
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Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.
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- Custom weights (e.g., fine-tuned checkpoints)
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- Custom input shapes
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- Target device and runtime configurations
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This option is ideal if you need to customize the model beyond the default configuration provided here.
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See our repository for [EfficientNet-V2-s on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.
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## Model Details
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## Performance Summary
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| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
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|---|---|---|---|---|---|---
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| EfficientNet-V2-s | ONNX | float | Snapdragon® X2 Elite |
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| EfficientNet-V2-s | ONNX | float | Snapdragon® X Elite | 5.
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| EfficientNet-V2-s | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 4.
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| EfficientNet-V2-s | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 11.
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| EfficientNet-V2-s | ONNX | float | Qualcomm® QCS8550 (Proxy) | 5.
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| EfficientNet-V2-s | ONNX | float | Qualcomm® QCS8450 | 11.
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| EfficientNet-V2-s | ONNX | float |
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| EfficientNet-V2-s | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.
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| EfficientNet-V2-s | ONNX | float |
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| EfficientNet-V2-s | ONNX | float | Qualcomm®
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| EfficientNet-V2-s | ONNX | float | Qualcomm®
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| EfficientNet-V2-s | ONNX | w8a16 | Snapdragon® X2 Elite | 2.
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| EfficientNet-V2-s | ONNX | w8a16 | Snapdragon® X Elite | 5.
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| EfficientNet-V2-s | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 3.
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| EfficientNet-V2-s | ONNX | w8a16 | Snapdragon® 8 Gen 1 Mobile | 6.
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| EfficientNet-V2-s | ONNX | w8a16 | Qualcomm® QCS6490 |
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| EfficientNet-V2-s | ONNX | w8a16 | Qualcomm® QCS8550 (Proxy) | 5.
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| EfficientNet-V2-s | ONNX | w8a16 | Qualcomm® QCS8450 | 6.
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| EfficientNet-V2-s | ONNX | w8a16 | Qualcomm®
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| EfficientNet-V2-s | ONNX | w8a16 | Snapdragon®
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| EfficientNet-V2-s | ONNX | w8a16 | Snapdragon® 8 Elite Mobile | 2.
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| EfficientNet-V2-s | ONNX | w8a16 |
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| EfficientNet-V2-s | ONNX | w8a16 |
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| EfficientNet-V2-s | ONNX | w8a16 | Qualcomm®
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| EfficientNet-V2-s | ONNX | w8a16 | Qualcomm®
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| EfficientNet-V2-s | ONNX | w8a16 | Qualcomm®
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| EfficientNet-V2-s | QNN_DLC | float | Snapdragon® X2 Elite | 3.
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| EfficientNet-V2-s | QNN_DLC | float | Snapdragon® X Elite | 6.
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| EfficientNet-V2-s | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 4.
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| EfficientNet-V2-s | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 13.
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm® QCS8275 | 25.
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 5.
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm®
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| EfficientNet-V2-s | QNN_DLC | float |
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm®
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| EfficientNet-V2-s | QNN_DLC | float |
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm®
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| EfficientNet-V2-s | QNN_DLC | float |
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm®
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| EfficientNet-V2-s | QNN_DLC | float |
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| EfficientNet-V2-s | QNN_DLC |
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| EfficientNet-V2-s | QNN_DLC |
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| EfficientNet-V2-s | QNN_DLC |
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Snapdragon®
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| EfficientNet-V2-s | QNN_DLC | w8a16 |
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| EfficientNet-V2-s | QNN_DLC | w8a16 |
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| EfficientNet-V2-s | QNN_DLC | w8a16 |
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm®
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm®
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| EfficientNet-V2-s | QNN_DLC | w8a16 |
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| EfficientNet-V2-s | QNN_DLC | w8a16 |
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm®
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| EfficientNet-V2-s | QNN_DLC | w8a16 |
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm®
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm®
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| EfficientNet-V2-s | QNN_DLC | w8a16 |
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| EfficientNet-V2-s | QNN_DLC | w8a16 |
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm®
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| EfficientNet-V2-s |
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| EfficientNet-V2-s |
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| EfficientNet-V2-s |
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| EfficientNet-V2-s |
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| EfficientNet-V2-s |
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| EfficientNet-V2-s |
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| EfficientNet-V2-s | TFLITE | float |
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| EfficientNet-V2-s | TFLITE | float |
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| EfficientNet-V2-s | TFLITE | float |
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| EfficientNet-V2-s | TFLITE | float | Qualcomm®
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| EfficientNet-V2-s | TFLITE | float |
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| EfficientNet-V2-s | TFLITE | float | Qualcomm®
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| EfficientNet-V2-s | TFLITE | float | Qualcomm®
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| EfficientNet-V2-s | TFLITE | float | Qualcomm®
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## License
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* The license for the original implementation of EfficientNet-V2-s can be found
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EfficientNetV2-s is a machine learning model that can classify images from the Imagenet dataset. It can also be used as a backbone in building more complex models for specific use cases.
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This is based on the implementation of EfficientNet-V2-s found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/efficientnet.py).
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+
This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.58.0/src/qai_hub_models/models/efficientnet_v2_s) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
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Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.
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| Runtime | Precision | Chipset | SDK Versions | Download |
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|---|---|---|---|---|
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| ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.25.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.58.0/efficientnet_v2_s-onnx-float.zip)
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| ONNX | w8a16 | Universal | QAIRT 2.45, ONNX Runtime 1.25.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.58.0/efficientnet_v2_s-onnx-w8a16.zip)
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| QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.58.0/efficientnet_v2_s-qnn_dlc-float.zip)
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| QNN_DLC | w8a16 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.58.0/efficientnet_v2_s-qnn_dlc-w8a16.zip)
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| TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.58.0/efficientnet_v2_s-tflite-float.zip)
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For more device-specific assets and performance metrics, visit **[EfficientNet-V2-s on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/efficientnet_v2_s)**.
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### Option 2: Export with Custom Configurations
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Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.58.0/src/qai_hub_models/models/efficientnet_v2_s) Python library to compile and export the model with your own:
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- Custom weights (e.g., fine-tuned checkpoints)
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- Custom input shapes
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- Target device and runtime configurations
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This option is ideal if you need to customize the model beyond the default configuration provided here.
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See our repository for [EfficientNet-V2-s on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.58.0/src/qai_hub_models/models/efficientnet_v2_s) for usage instructions.
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## Model Details
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## Performance Summary
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| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
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|---|---|---|---|---|---|---
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| EfficientNet-V2-s | ONNX | float | Snapdragon® X2 Elite | 3.035 ms | 2 - 2 MB | NPU
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| EfficientNet-V2-s | ONNX | float | Snapdragon® X Elite | 5.605 ms | 46 - 46 MB | NPU
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| EfficientNet-V2-s | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 4.061 ms | 0 - 165 MB | NPU
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| EfficientNet-V2-s | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 11.635 ms | 2 - 197 MB | NPU
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| EfficientNet-V2-s | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 5.347 ms | 0 - 49 MB | NPU
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| EfficientNet-V2-s | ONNX | float | Qualcomm® QCS8450 | 11.635 ms | 2 - 197 MB | NPU
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| EfficientNet-V2-s | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 7.625 ms | 1 - 6 MB | NPU
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| EfficientNet-V2-s | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.319 ms | 2 - 206 MB | NPU
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| EfficientNet-V2-s | ONNX | float | Snapdragon® 8 Elite Mobile | 3.1 ms | 0 - 202 MB | NPU
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| EfficientNet-V2-s | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 3.1 ms | 0 - 202 MB | NPU
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| EfficientNet-V2-s | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 5.605 ms | 46 - 46 MB | NPU
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| EfficientNet-V2-s | ONNX | w8a16 | Snapdragon® X2 Elite | 2.365 ms | 2 - 2 MB | NPU
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| EfficientNet-V2-s | ONNX | w8a16 | Snapdragon® X Elite | 5.739 ms | 24 - 24 MB | NPU
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| EfficientNet-V2-s | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 3.622 ms | 0 - 208 MB | NPU
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| EfficientNet-V2-s | ONNX | w8a16 | Snapdragon® 8 Gen 1 Mobile | 6.781 ms | 1 - 218 MB | NPU
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| EfficientNet-V2-s | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS6490 | 20.095 ms | 1 - 4 MB | NPU
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| EfficientNet-V2-s | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 5.47 ms | 0 - 249 MB | NPU
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| EfficientNet-V2-s | ONNX | w8a16 | Qualcomm® QCS8450 | 6.781 ms | 1 - 218 MB | NPU
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| EfficientNet-V2-s | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 5.734 ms | 1 - 4 MB | NPU
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| EfficientNet-V2-s | ONNX | w8a16 | Snapdragon® 7 Gen 4 Mobile | 6.428 ms | 1 - 273 MB | NPU
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| EfficientNet-V2-s | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 2.006 ms | 0 - 169 MB | NPU
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| EfficientNet-V2-s | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-6690 | 39.348 ms | 1 - 274 MB | NPU
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| EfficientNet-V2-s | ONNX | w8a16 | Snapdragon® 8 Elite Mobile | 2.51 ms | 0 - 164 MB | NPU
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| EfficientNet-V2-s | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-7790 | 6.428 ms | 1 - 273 MB | NPU
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| EfficientNet-V2-s | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 2.51 ms | 0 - 164 MB | NPU
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| EfficientNet-V2-s | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 5.739 ms | 24 - 24 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Snapdragon® X2 Elite | 3.43 ms | 2 - 2 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Snapdragon® X Elite | 6.381 ms | 2 - 2 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 4.335 ms | 0 - 158 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 13.484 ms | 0 - 188 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm® QCS8275 | 25.737 ms | 2 - 76 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 5.782 ms | 2 - 3 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm® SA8775P | 8.22 ms | 2 - 76 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm® SA8650P | 8.22 ms | 2 - 76 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm® SA8255P | 8.22 ms | 2 - 76 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm® QCS8450 | 13.484 ms | 0 - 188 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 7.911 ms | 4 - 7 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.361 ms | 2 - 85 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm® SA7255P | 25.737 ms | 2 - 76 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 3.133 ms | 2 - 80 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm® SA8295P | 12.985 ms | 2 - 108 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 3.133 ms | 2 - 80 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 6.381 ms | 2 - 2 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Snapdragon® X2 Elite | 2.86 ms | 1 - 1 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Snapdragon® X Elite | 6.8 ms | 1 - 1 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Snapdragon® 8 Gen 3 Mobile | 4.195 ms | 1 - 176 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Snapdragon® 8 Gen 1 Mobile | 8.155 ms | 1 - 185 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS6490 | 21.336 ms | 1 - 3 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm® QCS8275 | 12.069 ms | 1 - 134 MB | NPU
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| 115 |
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 6.231 ms | 1 - 2 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm® SA8775P | 6.7 ms | 1 - 137 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm® SA8650P | 6.7 ms | 1 - 137 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm® SA8255P | 6.7 ms | 1 - 137 MB | NPU
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| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm® QCS8450 | 8.155 ms | 1 - 185 MB | NPU
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| 120 |
+
| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 6.466 ms | 0 - 3 MB | NPU
|
| 121 |
+
| EfficientNet-V2-s | QNN_DLC | w8a16 | Snapdragon® 7 Gen 4 Mobile | 7.169 ms | 1 - 254 MB | NPU
|
| 122 |
+
| EfficientNet-V2-s | QNN_DLC | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 2.247 ms | 1 - 146 MB | NPU
|
| 123 |
+
| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-6690 | 41.217 ms | 1 - 255 MB | NPU
|
| 124 |
+
| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm® SA7255P | 12.069 ms | 1 - 134 MB | NPU
|
| 125 |
+
| EfficientNet-V2-s | QNN_DLC | w8a16 | Snapdragon® 8 Elite Mobile | 2.819 ms | 0 - 144 MB | NPU
|
| 126 |
+
| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm® SA8295P | 8.38 ms | 1 - 135 MB | NPU
|
| 127 |
+
| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-7790 | 7.169 ms | 1 - 254 MB | NPU
|
| 128 |
+
| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 2.819 ms | 0 - 144 MB | NPU
|
| 129 |
+
| EfficientNet-V2-s | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 6.8 ms | 1 - 1 MB | NPU
|
| 130 |
+
| EfficientNet-V2-s | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 4.327 ms | 0 - 199 MB | NPU
|
| 131 |
+
| EfficientNet-V2-s | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 13.528 ms | 0 - 228 MB | NPU
|
| 132 |
+
| EfficientNet-V2-s | TFLITE | float | Qualcomm® QCS8275 | 25.814 ms | 0 - 116 MB | NPU
|
| 133 |
+
| EfficientNet-V2-s | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 5.74 ms | 0 - 2 MB | NPU
|
| 134 |
+
| EfficientNet-V2-s | TFLITE | float | Qualcomm® SA8775P | 8.25 ms | 0 - 119 MB | NPU
|
| 135 |
+
| EfficientNet-V2-s | TFLITE | float | Qualcomm® SA8650P | 8.25 ms | 0 - 119 MB | NPU
|
| 136 |
+
| EfficientNet-V2-s | TFLITE | float | Qualcomm® SA8255P | 8.25 ms | 0 - 119 MB | NPU
|
| 137 |
+
| EfficientNet-V2-s | TFLITE | float | Qualcomm® QCS8450 | 13.528 ms | 0 - 228 MB | NPU
|
| 138 |
+
| EfficientNet-V2-s | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 7.914 ms | 0 - 51 MB | NPU
|
| 139 |
+
| EfficientNet-V2-s | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.339 ms | 0 - 121 MB | NPU
|
| 140 |
+
| EfficientNet-V2-s | TFLITE | float | Qualcomm® SA7255P | 25.814 ms | 0 - 116 MB | NPU
|
| 141 |
+
| EfficientNet-V2-s | TFLITE | float | Snapdragon® 8 Elite Mobile | 3.137 ms | 0 - 123 MB | NPU
|
| 142 |
+
| EfficientNet-V2-s | TFLITE | float | Qualcomm® SA8295P | 13.029 ms | 0 - 148 MB | NPU
|
| 143 |
+
| EfficientNet-V2-s | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 3.137 ms | 0 - 123 MB | NPU
|
| 144 |
|
| 145 |
## License
|
| 146 |
* The license for the original implementation of EfficientNet-V2-s can be found
|
release_assets.json
CHANGED
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| 1 |
{
|
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-
"version": "0.
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"precisions": {
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"w8a16": {
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"universal_assets": {
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"tool_versions": {
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| 8 |
"qairt": "2.45.0.260326154327"
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| 9 |
},
|
| 10 |
-
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.
|
| 11 |
},
|
| 12 |
"onnx": {
|
| 13 |
"tool_versions": {
|
| 14 |
"qairt": "2.45.0.260326154327",
|
| 15 |
"onnx_runtime": "1.25.0"
|
| 16 |
},
|
| 17 |
-
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.
|
| 18 |
}
|
| 19 |
}
|
| 20 |
},
|
|
@@ -25,20 +25,20 @@
|
|
| 25 |
"qairt": "2.45.0.260326154327",
|
| 26 |
"litert": "1.4.4"
|
| 27 |
},
|
| 28 |
-
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.
|
| 29 |
},
|
| 30 |
"qnn_dlc": {
|
| 31 |
"tool_versions": {
|
| 32 |
"qairt": "2.45.0.260326154327"
|
| 33 |
},
|
| 34 |
-
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.
|
| 35 |
},
|
| 36 |
"onnx": {
|
| 37 |
"tool_versions": {
|
| 38 |
"qairt": "2.45.0.260326154327",
|
| 39 |
"onnx_runtime": "1.25.0"
|
| 40 |
},
|
| 41 |
-
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.
|
| 42 |
}
|
| 43 |
}
|
| 44 |
}
|
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|
| 1 |
{
|
| 2 |
+
"version": "0.58.0",
|
| 3 |
"precisions": {
|
| 4 |
"w8a16": {
|
| 5 |
"universal_assets": {
|
|
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|
| 7 |
"tool_versions": {
|
| 8 |
"qairt": "2.45.0.260326154327"
|
| 9 |
},
|
| 10 |
+
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.58.0/efficientnet_v2_s-qnn_dlc-w8a16.zip"
|
| 11 |
},
|
| 12 |
"onnx": {
|
| 13 |
"tool_versions": {
|
| 14 |
"qairt": "2.45.0.260326154327",
|
| 15 |
"onnx_runtime": "1.25.0"
|
| 16 |
},
|
| 17 |
+
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.58.0/efficientnet_v2_s-onnx-w8a16.zip"
|
| 18 |
}
|
| 19 |
}
|
| 20 |
},
|
|
|
|
| 25 |
"qairt": "2.45.0.260326154327",
|
| 26 |
"litert": "1.4.4"
|
| 27 |
},
|
| 28 |
+
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.58.0/efficientnet_v2_s-tflite-float.zip"
|
| 29 |
},
|
| 30 |
"qnn_dlc": {
|
| 31 |
"tool_versions": {
|
| 32 |
"qairt": "2.45.0.260326154327"
|
| 33 |
},
|
| 34 |
+
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.58.0/efficientnet_v2_s-qnn_dlc-float.zip"
|
| 35 |
},
|
| 36 |
"onnx": {
|
| 37 |
"tool_versions": {
|
| 38 |
"qairt": "2.45.0.260326154327",
|
| 39 |
"onnx_runtime": "1.25.0"
|
| 40 |
},
|
| 41 |
+
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_v2_s/releases/v0.58.0/efficientnet_v2_s-onnx-float.zip"
|
| 42 |
}
|
| 43 |
}
|
| 44 |
}
|