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Albert-Base-V2-Hf

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metadata 
library_name: pytorch
license: other
tags:
  - backbone
  - android
pipeline_tag: text-generation

Albert-Base-V2-Hf: Optimized for Qualcomm Devices

ALBERT is a lightweight BERT model designed for efficient self-supervised learning of language representations. It can be used for masked language modeling and as a backbone for various NLP tasks.

This is based on the implementation of Albert-Base-V2-Hf 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
QNN_DLC float Universal QAIRT 2.42 Download
QNN_DLC w8a16 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 Albert-Base-V2-Hf 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 Albert-Base-V2-Hf on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.text_generation

Model Stats:

  • Model checkpoint: albert/albert-base-v2
  • Input resolution: 1x384
  • Number of parameters: 11.8M
  • Model size (float): 43.9 MB

Performance Summary

Model Runtime Precision Chipset Inference Time (ms) Peak Memory Range (MB) Primary Compute Unit
Albert-Base-V2-Hf ONNX float Snapdragon® X Elite 28.987 ms 33 - 33 MB NPU
Albert-Base-V2-Hf ONNX float Snapdragon® 8 Gen 3 Mobile 22.278 ms 0 - 385 MB NPU
Albert-Base-V2-Hf ONNX float Qualcomm® QCS8550 (Proxy) 30.096 ms 0 - 317 MB NPU
Albert-Base-V2-Hf ONNX float Qualcomm® QCS9075 32.316 ms 0 - 3 MB NPU
Albert-Base-V2-Hf ONNX float Snapdragon® 8 Elite For Galaxy Mobile 17.079 ms 0 - 326 MB NPU
Albert-Base-V2-Hf ONNX float Snapdragon® 8 Elite Gen 5 Mobile 14.437 ms 0 - 335 MB NPU
Albert-Base-V2-Hf QNN_DLC float Snapdragon® X Elite 22.358 ms 0 - 0 MB NPU
Albert-Base-V2-Hf QNN_DLC float Snapdragon® 8 Gen 3 Mobile 17.408 ms 0 - 375 MB NPU
Albert-Base-V2-Hf QNN_DLC float Qualcomm® QCS8275 (Proxy) 74.867 ms 0 - 317 MB NPU
Albert-Base-V2-Hf QNN_DLC float Qualcomm® QCS8550 (Proxy) 23.222 ms 0 - 2 MB NPU
Albert-Base-V2-Hf QNN_DLC float Qualcomm® SA8775P 27.658 ms 0 - 316 MB NPU
Albert-Base-V2-Hf QNN_DLC float Qualcomm® QCS9075 26.841 ms 0 - 2 MB NPU
Albert-Base-V2-Hf QNN_DLC float Qualcomm® QCS8450 (Proxy) 35.81 ms 0 - 421 MB NPU
Albert-Base-V2-Hf QNN_DLC float Qualcomm® SA7255P 74.867 ms 0 - 317 MB NPU
Albert-Base-V2-Hf QNN_DLC float Qualcomm® SA8295P 33.432 ms 0 - 376 MB NPU
Albert-Base-V2-Hf QNN_DLC float Snapdragon® 8 Elite For Galaxy Mobile 11.917 ms 0 - 386 MB NPU
Albert-Base-V2-Hf QNN_DLC float Snapdragon® 8 Elite Gen 5 Mobile 9.823 ms 0 - 391 MB NPU
Albert-Base-V2-Hf QNN_DLC w8a16 Snapdragon® X Elite 13.997 ms 0 - 0 MB NPU
Albert-Base-V2-Hf QNN_DLC w8a16 Snapdragon® 8 Gen 3 Mobile 9.558 ms 0 - 295 MB NPU
Albert-Base-V2-Hf QNN_DLC w8a16 Qualcomm® QCS8275 (Proxy) 29.59 ms 0 - 257 MB NPU
Albert-Base-V2-Hf QNN_DLC w8a16 Qualcomm® QCS8550 (Proxy) 13.542 ms 0 - 236 MB NPU
Albert-Base-V2-Hf QNN_DLC w8a16 Qualcomm® SA8775P 13.392 ms 0 - 249 MB NPU
Albert-Base-V2-Hf QNN_DLC w8a16 Qualcomm® QCS9075 15.845 ms 0 - 2 MB NPU
Albert-Base-V2-Hf QNN_DLC w8a16 Qualcomm® SA7255P 29.59 ms 0 - 257 MB NPU
Albert-Base-V2-Hf QNN_DLC w8a16 Snapdragon® 8 Elite For Galaxy Mobile 7.916 ms 0 - 248 MB NPU
Albert-Base-V2-Hf QNN_DLC w8a16 Snapdragon® 8 Elite Gen 5 Mobile 5.495 ms 0 - 265 MB NPU
Albert-Base-V2-Hf TFLITE float Snapdragon® 8 Gen 3 Mobile 17.443 ms 0 - 387 MB NPU
Albert-Base-V2-Hf TFLITE float Qualcomm® QCS8275 (Proxy) 74.61 ms 0 - 321 MB NPU
Albert-Base-V2-Hf TFLITE float Qualcomm® QCS8550 (Proxy) 22.268 ms 0 - 343 MB NPU
Albert-Base-V2-Hf TFLITE float Qualcomm® SA8775P 27.317 ms 0 - 321 MB NPU
Albert-Base-V2-Hf TFLITE float Qualcomm® QCS9075 27.14 ms 0 - 33 MB NPU
Albert-Base-V2-Hf TFLITE float Qualcomm® QCS8450 (Proxy) 40.475 ms 0 - 419 MB NPU
Albert-Base-V2-Hf TFLITE float Qualcomm® SA7255P 74.61 ms 0 - 321 MB NPU
Albert-Base-V2-Hf TFLITE float Qualcomm® SA8295P 34.418 ms 0 - 377 MB NPU
Albert-Base-V2-Hf TFLITE float Snapdragon® 8 Elite For Galaxy Mobile 12.431 ms 0 - 391 MB NPU
Albert-Base-V2-Hf TFLITE float Snapdragon® 8 Elite Gen 5 Mobile 10.065 ms 0 - 388 MB NPU

License

  • The license for the original implementation of Albert-Base-V2-Hf can be found here.

References

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