LISTENAI/linger

a CSK serial based train tools, rely on pytorch

49
/ 100
Emerging

This tool helps AI developers optimize neural network models for embedded devices. It takes your existing PyTorch floating-point neural network models and converts them into smaller, more efficient 8-bit quantized models. AI developers working on deploying models to low-power IoT chips will find this particularly useful.

Use this if you need to reduce the size and computational requirements of your PyTorch-trained AI models for deployment on resource-constrained hardware like IoT chips, without significantly losing accuracy.

Not ideal if you are not working with PyTorch models or if your primary goal is not model quantization for embedded systems.

AI model optimization embedded AI IoT deep learning neural network deployment model quantization
No Package No Dependents
Maintenance 10 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 16 / 25

How are scores calculated?

Stars

29

Forks

6

Language

Python

License

Apache-2.0

Last pushed

Feb 06, 2026

Commits (30d)

0

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