Qualcomm® AI Hub simplifies deploying AI models for vision, audio, and speech applications to edge devices.
helps to optimize, validate, and deploy machine learning models on-device for vision, audio, and speech use cases.
With Qualcomm® AI Model Hub, you can:
Convert trained models from frameworks like PyTorch for optimized on-device performance on Qualcomm® devices.
Profile models on-device to obtain detailed metrics including runtime, load time, and compute unit utilization.
Verify numerical correctness by performing on-device inference.
Easily deploy models using Qualcomm® AI Engine Direct or TensorFlow Lite.
qai_hub is a python package that provides an API for users to upload a
model, submit the profile jobs for hardware and get key metrics to optimize the
machine learning model further.
Installation with PyPI
The easiest way to install qai_hub is by using pip, running
pip install qai-hub
For more information, check out the documentation.
License
Copyright (c) 2023, Qualcomm Technologies Inc. All rights reserved.
1 maintainer
Release files for qai-hub 0.55.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| qai_hub-0.55.0-py3-none-any.whl | Python 3 | none | any | Details |
Release files / qai_hub-0.55.0-py3-none-any.whl
| Download URL | qai_hub-0.55.0-py3-none-any.whl |
|---|---|
| Size | 131.9 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
caf3966538cbcc50b69b781a4071d7c5a9ec560c2888647b5b74420f213cfe9b
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BLAKE2b-256 checksum How to use checksums |
63e23ae35d4e93b086f85dc04e6b729354833e0f5b99b14234a04fbd78fb9a2b
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.3
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