library_name: pytorch
license: other
tags:
- android
pipeline_tag: image-classification
Sequencer2D: Optimized for Qualcomm Devices
Sequencer2D is a vision transformer model that can classify images from the Imagenet dataset.
This is based on the implementation of Sequencer2D found here. This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the Qualcomm® AI Hub Models library to export with custom configurations. More details on model performance across various devices, can be found here.
Qualcomm AI Hub Models uses Qualcomm AI Hub Workbench to compile, profile, and evaluate this model. Sign up to run these models on a hosted Qualcomm® device.
Getting Started
There are two ways to deploy this model on your device:
Option 1: Download Pre-Exported Models
Below are pre-exported model assets ready for deployment.
| Runtime | Precision | Chipset | SDK Versions | Download |
|---|---|---|---|---|
| ONNX | float | Universal | QAIRT 2.37, ONNX Runtime 1.23.0 | Download |
| ONNX | w8a16 | Universal | QAIRT 2.37, ONNX Runtime 1.23.0 | Download |
| QNN_DLC | float | Universal | QAIRT 2.42 | Download |
| TFLITE | float | Universal | QAIRT 2.42, TFLite 2.17.0 | Download |
For more device-specific assets and performance metrics, visit Sequencer2D on Qualcomm® AI Hub.
Option 2: Export with Custom Configurations
Use the Qualcomm® AI Hub Models Python library to compile and export the model with your own:
- Custom weights (e.g., fine-tuned checkpoints)
- Custom input shapes
- Target device and runtime configurations
This option is ideal if you need to customize the model beyond the default configuration provided here.
See our repository for Sequencer2D on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.image_classification
Model Stats:
- Model checkpoint: sequencer2d_s
- Input resolution: 224x224
- Number of parameters: 27.6M
- Model size (float): 106 MB
- Model size (w8a8): 69.1 MB
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| Sequencer2D | ONNX | float | Snapdragon® X Elite | 48.401 ms | 66 - 66 MB | NPU |
| Sequencer2D | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 33.466 ms | 1 - 1349 MB | NPU |
| Sequencer2D | ONNX | float | Qualcomm® QCS8550 (Proxy) | 46.558 ms | 0 - 83 MB | NPU |
| Sequencer2D | ONNX | float | Qualcomm® QCS9075 | 57.399 ms | 0 - 4 MB | NPU |
| Sequencer2D | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 23.058 ms | 1 - 766 MB | NPU |
| Sequencer2D | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 17.991 ms | 1 - 807 MB | NPU |
| Sequencer2D | ONNX | w8a16 | Snapdragon® X Elite | 123.498 ms | 132 - 132 MB | NPU |
| Sequencer2D | ONNX | w8a16 | Qualcomm® QCS6490 | 647.033 ms | 46 - 56 MB | CPU |
| Sequencer2D | ONNX | w8a16 | Qualcomm® QCS9075 | 165.125 ms | 107 - 110 MB | NPU |
| Sequencer2D | ONNX | w8a16 | Qualcomm® QCM6690 | 274.09 ms | 47 - 63 MB | CPU |
| Sequencer2D | ONNX | w8a16 | Snapdragon® 8 Elite For Galaxy Mobile | 105.431 ms | 106 - 488 MB | NPU |
| Sequencer2D | ONNX | w8a16 | Snapdragon® 7 Gen 4 Mobile | 260.838 ms | 26 - 37 MB | CPU |
| Sequencer2D | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 102.361 ms | 50 - 436 MB | NPU |
| Sequencer2D | QNN_DLC | float | Snapdragon® X Elite | 21.419 ms | 1 - 1 MB | NPU |
| Sequencer2D | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 14.292 ms | 0 - 2279 MB | NPU |
| Sequencer2D | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 20.806 ms | 1 - 565 MB | NPU |
| Sequencer2D | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 26.272 ms | 0 - 846 MB | NPU |
| Sequencer2D | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 12.521 ms | 1 - 1065 MB | NPU |
| Sequencer2D | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 9.34 ms | 0 - 1225 MB | NPU |
| Sequencer2D | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 11.933 ms | 0 - 917 MB | NPU |
| Sequencer2D | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 37.369 ms | 0 - 810 MB | NPU |
| Sequencer2D | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 17.044 ms | 0 - 12 MB | NPU |
| Sequencer2D | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 21.299 ms | 0 - 724 MB | NPU |
| Sequencer2D | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 9.406 ms | 0 - 744 MB | NPU |
| Sequencer2D | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 7.34 ms | 0 - 1082 MB | NPU |
License
- The license for the original implementation of Sequencer2D can be found here.
References
Community
- Join our AI Hub Slack community to collaborate, post questions and learn more about on-device AI.
- For questions or feedback please reach out to us.