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README.md
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| Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
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| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 1.
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| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 1.
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## Installation
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python -m qai_hub_models.models.googlenet.export
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```
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```
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Profile Job summary of GoogLeNet
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Device: Samsung Galaxy S24 (14)
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Estimated Inference Time: 0.69 ms
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Estimated Peak Memory Range: 0.01-43.58 MB
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Compute Units: NPU (84) | Total (84)
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Profile Job summary of GoogLeNet
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Device: Samsung Galaxy S24 (14)
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Estimated Inference Time: 0.69 ms
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Estimated Peak Memory Range: 0.59-51.77 MB
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Compute Units: NPU (143) | Total (143)
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```
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## How does this work?
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This [export script](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/GoogLeNet/export.py)
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| Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
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| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 1.044 ms | 0 - 2 MB | FP16 | NPU | [GoogLeNet.tflite](https://huggingface.co/qualcomm/GoogLeNet/blob/main/GoogLeNet.tflite)
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| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 1.075 ms | 0 - 25 MB | FP16 | NPU | [GoogLeNet.so](https://huggingface.co/qualcomm/GoogLeNet/blob/main/GoogLeNet.so)
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## Installation
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python -m qai_hub_models.models.googlenet.export
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```
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## How does this work?
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This [export script](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/GoogLeNet/export.py)
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