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 2.42, ONNX Runtime 1.24.3	Download
QNN_DLC	float	Universal	QAIRT 2.43	Download
TFLITE	float	Universal	QAIRT 2.43, TFLite 2.19.1	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® 8 Elite Gen 5 Mobile	7.689 ms	0 - 481 MB	NPU
Electra-Bert-Base-Discrim-Google	ONNX	float	Snapdragon® X2 Elite	8.469 ms	220 - 220 MB	NPU
Electra-Bert-Base-Discrim-Google	ONNX	float	Snapdragon® X Elite	23.298 ms	220 - 220 MB	NPU
Electra-Bert-Base-Discrim-Google	ONNX	float	Snapdragon® 8 Gen 3 Mobile	15.951 ms	0 - 488 MB	NPU
Electra-Bert-Base-Discrim-Google	ONNX	float	Qualcomm® QCS8550 (Proxy)	22.587 ms	0 - 736 MB	NPU
Electra-Bert-Base-Discrim-Google	ONNX	float	Qualcomm® QCS9075	28.81 ms	0 - 3 MB	NPU
Electra-Bert-Base-Discrim-Google	ONNX	float	Snapdragon® 8 Elite For Galaxy Mobile	10.793 ms	0 - 482 MB	NPU
Electra-Bert-Base-Discrim-Google	QNN_DLC	float	Snapdragon® 8 Elite Gen 5 Mobile	5.722 ms	0 - 449 MB	NPU
Electra-Bert-Base-Discrim-Google	QNN_DLC	float	Snapdragon® X2 Elite	6.84 ms	1 - 1 MB	NPU
Electra-Bert-Base-Discrim-Google	QNN_DLC	float	Snapdragon® X Elite	18.127 ms	0 - 0 MB	NPU
Electra-Bert-Base-Discrim-Google	QNN_DLC	float	Snapdragon® 8 Gen 3 Mobile	12.013 ms	51 - 550 MB	NPU
Electra-Bert-Base-Discrim-Google	QNN_DLC	float	Qualcomm® QCS8275 (Proxy)	66.961 ms	0 - 419 MB	NPU
Electra-Bert-Base-Discrim-Google	QNN_DLC	float	Qualcomm® QCS8550 (Proxy)	17.386 ms	0 - 2 MB	NPU
Electra-Bert-Base-Discrim-Google	QNN_DLC	float	Qualcomm® SA8775P	21.331 ms	0 - 419 MB	NPU
Electra-Bert-Base-Discrim-Google	QNN_DLC	float	Qualcomm® QCS9075	22.044 ms	2 - 4 MB	NPU
Electra-Bert-Base-Discrim-Google	QNN_DLC	float	Qualcomm® QCS8450 (Proxy)	24.894 ms	0 - 452 MB	NPU
Electra-Bert-Base-Discrim-Google	QNN_DLC	float	Qualcomm® SA7255P	66.961 ms	0 - 419 MB	NPU
Electra-Bert-Base-Discrim-Google	QNN_DLC	float	Qualcomm® SA8295P	26.543 ms	0 - 374 MB	NPU
Electra-Bert-Base-Discrim-Google	QNN_DLC	float	Snapdragon® 8 Elite For Galaxy Mobile	8.143 ms	0 - 449 MB	NPU
Electra-Bert-Base-Discrim-Google	TFLITE	float	Snapdragon® 8 Elite Gen 5 Mobile	5.748 ms	0 - 454 MB	NPU
Electra-Bert-Base-Discrim-Google	TFLITE	float	Snapdragon® 8 Gen 3 Mobile	12.023 ms	0 - 497 MB	NPU
Electra-Bert-Base-Discrim-Google	TFLITE	float	Qualcomm® QCS8275 (Proxy)	66.966 ms	0 - 420 MB	NPU
Electra-Bert-Base-Discrim-Google	TFLITE	float	Qualcomm® QCS8550 (Proxy)	16.685 ms	0 - 2 MB	NPU
Electra-Bert-Base-Discrim-Google	TFLITE	float	Qualcomm® SA8775P	21.362 ms	1 - 421 MB	NPU
Electra-Bert-Base-Discrim-Google	TFLITE	float	Qualcomm® QCS9075	22.354 ms	0 - 213 MB	NPU
Electra-Bert-Base-Discrim-Google	TFLITE	float	Qualcomm® QCS8450 (Proxy)	24.996 ms	0 - 448 MB	NPU
Electra-Bert-Base-Discrim-Google	TFLITE	float	Qualcomm® SA7255P	66.966 ms	0 - 420 MB	NPU
Electra-Bert-Base-Discrim-Google	TFLITE	float	Qualcomm® SA8295P	26.47 ms	0 - 374 MB	NPU
Electra-Bert-Base-Discrim-Google	TFLITE	float	Snapdragon® 8 Elite For Galaxy Mobile	8.039 ms	0 - 457 MB	NPU

License

The license for the original implementation of Electra-Bert-Base-Discrim-Google can be found here.

References

Community

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Paper for qualcomm/Electra-Bert-Base-Discrim-Google

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

Paper • 2003.10555 • Published Mar 23, 2020