--- library_name: pytorch license: other tags: - backbone - android pipeline_tag: image-classification --- ![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/beit/web-assets/model_demo.png) # Beit: Optimized for Qualcomm Devices Beit 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. This is based on the implementation of Beit found [here](https://github.com/microsoft/unilm/tree/master/beit). 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/beit) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary). 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. ## 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 2.45, ONNX Runtime 1.25.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/beit/releases/v0.58.0/beit-onnx-float.zip) | 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/beit/releases/v0.58.0/beit-onnx-w8a16.zip) | QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/beit/releases/v0.58.0/beit-qnn_dlc-float.zip) | QNN_DLC | w8a16 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/beit/releases/v0.58.0/beit-qnn_dlc-w8a16.zip) | TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/beit/releases/v0.58.0/beit-tflite-float.zip) For more device-specific assets and performance metrics, visit **[Beit on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/beit)**. ### Option 2: Export with Custom Configurations Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.58.0/src/qai_hub_models/models/beit) 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 [Beit on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.58.0/src/qai_hub_models/models/beit) for usage instructions. ## Model Details **Model Type:** Model_use_case.image_classification **Model Stats:** - Model checkpoint: Imagenet - Input resolution: 224x224 - Number of parameters: 92.0M - Model size (float): 351 MB ## Performance Summary | Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |---|---|---|---|---|---|--- | Beit | ONNX | float | Snapdragon® X2 Elite | 7.441 ms | 2 - 2 MB | NPU | Beit | ONNX | float | Snapdragon® X Elite | 15.354 ms | 184 - 184 MB | NPU | Beit | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 10.47 ms | 0 - 449 MB | NPU | Beit | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 17.99 ms | 0 - 421 MB | NPU | Beit | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 14.888 ms | 0 - 63 MB | NPU | Beit | ONNX | float | Qualcomm® QCS8450 | 17.99 ms | 0 - 421 MB | NPU | Beit | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 17.934 ms | 0 - 4 MB | NPU | Beit | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 7.169 ms | 0 - 307 MB | NPU | Beit | ONNX | float | Snapdragon® 8 Elite Mobile | 8.582 ms | 1 - 305 MB | NPU | Beit | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 8.582 ms | 1 - 305 MB | NPU | Beit | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 15.354 ms | 184 - 184 MB | NPU | Beit | ONNX | w8a16 | Snapdragon® X2 Elite | 2.669 ms | 1 - 1 MB | NPU | Beit | ONNX | w8a16 | Snapdragon® X Elite | 6.898 ms | 95 - 95 MB | NPU | Beit | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 4.576 ms | 0 - 422 MB | NPU | Beit | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 6.678 ms | 0 - 99 MB | NPU | Beit | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 6.621 ms | 0 - 3 MB | NPU | Beit | ONNX | w8a16 | Snapdragon® 7 Gen 4 Mobile | 9.054 ms | 0 - 412 MB | NPU | Beit | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 2.396 ms | 0 - 257 MB | NPU | Beit | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-6690 | 109.293 ms | 0 - 443 MB | NPU | Beit | ONNX | w8a16 | Snapdragon® 8 Elite Mobile | 3.593 ms | 0 - 361 MB | NPU | Beit | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-7790 | 9.054 ms | 0 - 412 MB | NPU | Beit | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 3.593 ms | 0 - 361 MB | NPU | Beit | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 6.898 ms | 95 - 95 MB | NPU | Beit | QNN_DLC | float | Snapdragon® X2 Elite | 7.853 ms | 1 - 1 MB | NPU | Beit | QNN_DLC | float | Snapdragon® X Elite | 15.165 ms | 1 - 1 MB | NPU | Beit | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 10.476 ms | 0 - 395 MB | NPU | Beit | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 17.553 ms | 0 - 380 MB | NPU | Beit | QNN_DLC | float | Qualcomm® QCS8275 | 48.01 ms | 1 - 295 MB | NPU | Beit | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 14.383 ms | 1 - 3 MB | NPU | Beit | QNN_DLC | float | Qualcomm® SA8775P | 17.18 ms | 1 - 295 MB | NPU | Beit | QNN_DLC | float | Qualcomm® SA8650P | 17.18 ms | 1 - 295 MB | NPU | Beit | QNN_DLC | float | Qualcomm® SA8255P | 17.18 ms | 1 - 295 MB | NPU | Beit | QNN_DLC | float | Qualcomm® QCS8450 | 17.553 ms | 0 - 380 MB | NPU | Beit | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 17.494 ms | 3 - 5 MB | NPU | Beit | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 7.184 ms | 1 - 301 MB | NPU | Beit | QNN_DLC | float | Qualcomm® SA7255P | 48.01 ms | 1 - 295 MB | NPU | Beit | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 8.576 ms | 1 - 301 MB | NPU | Beit | QNN_DLC | float | Qualcomm® SA8295P | 15.302 ms | 1 - 289 MB | NPU | Beit | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 8.576 ms | 1 - 301 MB | NPU | Beit | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 15.165 ms | 1 - 1 MB | NPU | Beit | QNN_DLC | w8a16 | Snapdragon® X2 Elite | 3.19 ms | 0 - 0 MB | NPU | Beit | QNN_DLC | w8a16 | Snapdragon® X Elite | 7.332 ms | 0 - 0 MB | NPU | Beit | QNN_DLC | w8a16 | Snapdragon® 8 Gen 3 Mobile | 4.671 ms | 0 - 413 MB | NPU | Beit | QNN_DLC | w8a16 | Qualcomm® QCS8275 | 15.088 ms | 0 - 351 MB | NPU | Beit | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 6.773 ms | 0 - 2 MB | NPU | Beit | QNN_DLC | w8a16 | Qualcomm® SA8775P | 7.054 ms | 0 - 352 MB | NPU | Beit | QNN_DLC | w8a16 | Qualcomm® SA8650P | 7.054 ms | 0 - 352 MB | NPU | Beit | QNN_DLC | w8a16 | Qualcomm® SA8255P | 7.054 ms | 0 - 352 MB | NPU | Beit | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 7.12 ms | 0 - 2 MB | NPU | Beit | QNN_DLC | w8a16 | Snapdragon® 7 Gen 4 Mobile | 8.687 ms | 0 - 399 MB | NPU | Beit | QNN_DLC | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 2.559 ms | 0 - 245 MB | NPU | Beit | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-6690 | 109.915 ms | 0 - 428 MB | NPU | Beit | QNN_DLC | w8a16 | Qualcomm® SA7255P | 15.088 ms | 0 - 351 MB | NPU | Beit | QNN_DLC | w8a16 | Snapdragon® 8 Elite Mobile | 3.589 ms | 0 - 349 MB | NPU | Beit | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-7790 | 8.687 ms | 0 - 399 MB | NPU | Beit | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 3.589 ms | 0 - 349 MB | NPU | Beit | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 7.332 ms | 0 - 0 MB | NPU | Beit | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 10.515 ms | 0 - 406 MB | NPU | Beit | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 17.546 ms | 0 - 371 MB | NPU | Beit | TFLITE | float | Qualcomm® QCS8275 | 48.061 ms | 0 - 300 MB | NPU | Beit | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 14.002 ms | 0 - 3 MB | NPU | Beit | TFLITE | float | Qualcomm® SA8775P | 17.189 ms | 0 - 301 MB | NPU | Beit | TFLITE | float | Qualcomm® SA8650P | 17.189 ms | 0 - 301 MB | NPU | Beit | TFLITE | float | Qualcomm® SA8255P | 17.189 ms | 0 - 301 MB | NPU | Beit | TFLITE | float | Qualcomm® QCS8450 | 17.546 ms | 0 - 371 MB | NPU | Beit | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 17.528 ms | 0 - 186 MB | NPU | Beit | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 7.18 ms | 0 - 311 MB | NPU | Beit | TFLITE | float | Qualcomm® SA7255P | 48.061 ms | 0 - 300 MB | NPU | Beit | TFLITE | float | Snapdragon® 8 Elite Mobile | 8.573 ms | 0 - 311 MB | NPU | Beit | TFLITE | float | Qualcomm® SA8295P | 15.345 ms | 0 - 293 MB | NPU | Beit | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 8.573 ms | 0 - 311 MB | NPU ## License * The license for the original implementation of Beit can be found [here](https://github.com/pytorch/vision/blob/main/LICENSE). ## References * [BEIT: BERT Pre-Training of Image Transformers](https://arxiv.org/abs/2106.08254) * [Source Model Implementation](https://github.com/microsoft/unilm/tree/master/beit) ## Community * Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI. * For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com).