Electra-Bert-Base-Discrim-Google: Optimized for Qualcomm Devices
ELECTRABERT is a lightweight BERT model designed for efficient self-supervised learning of language representations. It can be used for identify unnatural or artificially modified text and as a backbone for various NLP tasks.
This is based on the implementation of Electra-Bert-Base-Discrim-Google 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 2.45, ONNX Runtime 1.27.1 | Download |
| QNN_DLC | float | Universal | QAIRT 2.45 | Download |
| TFLITE | float | Universal | QAIRT 2.45 | Download |
For more device-specific assets and performance metrics, visit Electra-Bert-Base-Discrim-Google 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 Electra-Bert-Base-Discrim-Google on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.text_generation
Model Stats:
- Model checkpoint: google/electra-base-discriminator
- Input resolution: 1x384
- Number of parameters: 109M
- Model size (float): 417 MB
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| Electra-Bert-Base-Discrim-Google | ONNX | float | Snapdragon® X2 Elite | 8.395 ms | 1 - 1 MB | NPU |
| Electra-Bert-Base-Discrim-Google | ONNX | float | Snapdragon® X Elite | 23.177 ms | 219 - 219 MB | NPU |
| Electra-Bert-Base-Discrim-Google | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 16.274 ms | 0 - 433 MB | NPU |
| Electra-Bert-Base-Discrim-Google | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 32.192 ms | 0 - 405 MB | NPU |
| Electra-Bert-Base-Discrim-Google | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 22.525 ms | 0 - 247 MB | NPU |
| Electra-Bert-Base-Discrim-Google | ONNX | float | Qualcomm® QCS8450 | 32.192 ms | 0 - 405 MB | NPU |
| Electra-Bert-Base-Discrim-Google | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 27.457 ms | 0 - 3 MB | NPU |
| Electra-Bert-Base-Discrim-Google | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 23.177 ms | 219 - 219 MB | NPU |
| Electra-Bert-Base-Discrim-Google | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 10.799 ms | 0 - 370 MB | NPU |
| Electra-Bert-Base-Discrim-Google | ONNX | float | Snapdragon® 8 Elite Mobile | 10.799 ms | 0 - 370 MB | NPU |
| Electra-Bert-Base-Discrim-Google | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 7.629 ms | 0 - 376 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Snapdragon® X2 Elite | 6.868 ms | 0 - 0 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Snapdragon® X Elite | 17.98 ms | 0 - 0 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 11.826 ms | 0 - 432 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 24.949 ms | 0 - 384 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8275 | 66.776 ms | 0 - 308 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 17.039 ms | 0 - 4 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Qualcomm® SA8775P | 21.244 ms | 0 - 309 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Qualcomm® SA8650P | 21.244 ms | 0 - 309 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Qualcomm® SA8255P | 21.244 ms | 0 - 309 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Qualcomm® QCS8450 | 24.949 ms | 0 - 384 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 21.336 ms | 2 - 4 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 17.98 ms | 0 - 0 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 8.076 ms | 0 - 331 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Qualcomm® SA7255P | 66.776 ms | 0 - 308 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Qualcomm® SA8295P | 26.604 ms | 0 - 260 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 8.076 ms | 0 - 331 MB | NPU |
| Electra-Bert-Base-Discrim-Google | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 5.794 ms | 0 - 332 MB | NPU |
| Electra-Bert-Base-Discrim-Google | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 11.831 ms | 0 - 431 MB | NPU |
| Electra-Bert-Base-Discrim-Google | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 24.988 ms | 0 - 387 MB | NPU |
| Electra-Bert-Base-Discrim-Google | TFLITE | float | Qualcomm® Dragonwing™ QCS8275 | 66.861 ms | 0 - 309 MB | NPU |
| Electra-Bert-Base-Discrim-Google | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 16.454 ms | 0 - 2 MB | NPU |
| Electra-Bert-Base-Discrim-Google | TFLITE | float | Qualcomm® SA8775P | 21.319 ms | 0 - 311 MB | NPU |
| Electra-Bert-Base-Discrim-Google | TFLITE | float | Qualcomm® SA8650P | 21.319 ms | 0 - 311 MB | NPU |
| Electra-Bert-Base-Discrim-Google | TFLITE | float | Qualcomm® SA8255P | 21.319 ms | 0 - 311 MB | NPU |
| Electra-Bert-Base-Discrim-Google | TFLITE | float | Qualcomm® QCS8450 | 24.988 ms | 0 - 387 MB | NPU |
| Electra-Bert-Base-Discrim-Google | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 21.42 ms | 0 - 214 MB | NPU |
| Electra-Bert-Base-Discrim-Google | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 8.039 ms | 0 - 336 MB | NPU |
| Electra-Bert-Base-Discrim-Google | TFLITE | float | Qualcomm® SA7255P | 66.861 ms | 0 - 309 MB | NPU |
| Electra-Bert-Base-Discrim-Google | TFLITE | float | Qualcomm® SA8295P | 26.605 ms | 0 - 262 MB | NPU |
| Electra-Bert-Base-Discrim-Google | TFLITE | float | Snapdragon® 8 Elite Mobile | 8.039 ms | 0 - 336 MB | NPU |
| Electra-Bert-Base-Discrim-Google | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 5.8 ms | 0 - 338 MB | NPU |
License
- The license for the original implementation of Electra-Bert-Base-Discrim-Google can be found here.
References
- ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
- Source Model Implementation
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.
